CMS 2016 Projects (NRA 2015)


 

Baccini (CMS 2015) (2016)
Project Title:Time-Series Measurements of Biomass Change from InSAR (TanDEM-X), MODIS, and LiDAR Observations

Science Team
Members:

Alessandro (Ale) Baccini, Boston University (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2015)
Abstract: Deforestation and forest degradation of tropical vegetation account for 6 -17% of global annual CO2 emissions to the atmosphere (Van der Werf et al. 2009). International policy mechanisms designed to address emissions from forest loss such as REDD+ require the ability to monitor not only emissions from deforestation but also from forest degradation as well as the uptake by vegetation. While much progress has been made in monitoring changes in forest area and carbon density, measurements of biomass loss due to deforestation and degradation, and increases due to uptake remain challenging. Here we propose to develop a novel methodology to monitor CO2 fluxes to the atmosphere from losses (due to deforestation and degradation) and gains (from vegetation uptake) for the Amazon Basin. The approach is based on a combination of the InSAR TanDEM-x Spaceborne Interferometer, MODIS, LiDAR and field measurements. The overall objective of the proposed project is to address the research and development required for a multi-sensor, multi-spatial resolution monitoring system integrated with a carbon bookkeeping model to quantify CO2 fluxes to the atmosphere from land carbon dynamics. The specific objectives are to: 1) Quantify the correspondence between TanDEM-X phase height and biomass and derive biomass changes as a function of phase height variations. Using TanDEM-X data taken monthly and at 50-m resolution over Tapajos forest between 2011 and 2016, we will then determine the accuracy with which multi-temporal TanDEM-X observations can be used to measure biomass changes (losses and gains). To do this we will use existing field data and LiDAR measurements collected in the region; 2) assess the within-pixel sensitivity of MODIS derived biomass changes. We will build on Baccini et al. (2012; In Review) and derive annual biomass change estimates. We will then compare with high resolution change estimates from TanDEM-X and assess the sensitivity of MODIS to sub-pixel changes in biomass; 3) address the research and development required to combine InSAR spaceborne observations with MODIS reflectance. By combining time series of InSAR and MODIS observations we expect to increase the sensitivity in biomass change while expanding our monitoring capability over larger area; 4) assess the impact of differing resolutions and accuracies in biomass change estimates when products from objectives (1) and (3) are used in a bookkeeping model to derive CO2 fluxes.
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • MRV

Participants:

Alessandro (Ale) Baccini, Boston University
Robert Treuhaft, Jet Propulsion Laboratory / Caltech
Wayne Walker, Woodwell Climate Research Center

Project URL(s): None provided.
 
Data
Products:
Product Title:  Annual aboveground biomass density maps
Time Period:  2003-2018
Description:  
Status:  On-going
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Biomass density
Spatial Extent:  Tapajos Forest, Para, Brazil and Amazon Basin
Spatial Resolution:  500 m
Temporal Frequency:  Annual
Input Data Products:  InSAR TanDEM-x Spaceborne Interferometer, MODIS, LiDAR, and field measurements
Algorithm/Models Used:  Machine learning (RandomForest) Baccini et al. 2012
Evaluation:  Field and airborne LiDAR estimates
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Spatially explicit uncertainty estimates for each annual product
Uncertainty Categories:  
Application Areas:  Research, quantification of biomass/carbon pools, REDD+
Relevant Policies/Programs:  REDD+
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  4
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Annual estimates of aboveground biomass dynamics
Time Period:  2003-2018
Description:  
Status:  On-going
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Biomass change
Spatial Extent:  Tapajos Forest, Para, Brazil and Amazon Basin
Spatial Resolution:  500 m
Temporal Frequency:  Annual
Input Data Products:  InSAR TanDEM-x Spaceborne Interferometer, MODIS, LiDAR, and field measurements
Algorithm/Models Used:  Machine learning, change points algorithm (Baccini et al. 2017
Evaluation:  InSAR TanDEM-x change product
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Spatially explicit uncertainty estimates (Confidence Interval and P-Value)
Uncertainty Categories:  
Application Areas:  Carbon cycle science, REDD+, land restoration
Relevant Policies/Programs:  REDD+
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  4
Start Application Readiness Level:  2
Target Application Readiness Level:  5
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Error estimates for remote sensing based products
Time Period:  2011-2016
Description:  
Status:  Public
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Crown area, forest density, forest degradation, aboveground biomass, InSar
Spatial Extent:  Tapajos Forest, Para, Brazil
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  InSAR TanDEM-x Spaceborne Interferometer, LiDAR, and field measurements
Algorithm/Models Used:  
Evaluation:  Field measurements
Intercomparison Efforts/Gaps:  Comparison with field data
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  Research
Relevant Policies/Programs:  Carbon monitoring, carbon cycle science
Potential Users:  Researchers
Stakeholders:  
Current Application Readiness Level:  3
Start Application Readiness Level:  1
Target Application Readiness Level:  3
Future Developments:  
Limitations:  Difficult to extend to other region or time period because of InSAR data access policy
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  InSAR phase-height-rate algorithm
Time Period:  2011-2016
Description:  
Status:  Public
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Aboveground biomass, biomass dynamics, InSar
Spatial Extent:  Tapajos Forest, Para, Brazil
Spatial Resolution:  50 m to 250 m
Temporal Frequency:  Monthly
Input Data Products:  InSAR TanDEM-x Spaceborne Interferometer, LiDAR, and field measurements
Algorithm/Models Used:  
Evaluation:  Field measurements
Intercomparison Efforts/Gaps:  Comparison with MODIS based product and field data
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  Research, project level monitoring contingent to InSAR data availability
Relevant Policies/Programs:  REDD+, carbon monitoring, carbon cycle science
Potential Users:  Researchers, local stakeholders
Stakeholders:  
Current Application Readiness Level:  4
Start Application Readiness Level:  2
Target Application Readiness Level:  4
Future Developments:  
Limitations:  Difficult to extend to other region or time period because of InSAR data access policy
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  InSAR phase-height-rate algorithm (Simulation-based algorithm)
Time Period:  2011-2016
Description:  
Status:  Public
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Crown area, forest density, forest degradation, aboveground biomass, InSar
Spatial Extent:  Tapajos Forest, Para, Brazil
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  InSAR TanDEM-x Spaceborne Interferometer, LiDAR, and field measurements
Algorithm/Models Used:  
Evaluation:  Field measurements
Intercomparison Efforts/Gaps:  Comparison with field data
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  Research
Relevant Policies/Programs:  Carbon monitoring, carbon cycle science
Potential Users:  Researchers
Stakeholders:  
Current Application Readiness Level:  3
Start Application Readiness Level:  1
Target Application Readiness Level:  3
Future Developments:  
Limitations:  Difficult to extend to other region or time period because of InSAR data access policy
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  InSAR phase-height-rate algorithm (table)
Time Period:  2011-2016
Description:  
Status:  Public
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Aboveground biomass, biomass dynamics, InSar
Spatial Extent:  Tapajos Forest, Para, Brazil
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  InSAR TanDEM-x Spaceborne Interferometer, LiDAR, and field measurements
Algorithm/Models Used:  
Evaluation:  Field measurements
Intercomparison Efforts/Gaps:  Comparison with field data
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  Research, project level monitoring contingent to InSAR data availability
Relevant Policies/Programs:  REDD+, carbon monitoring, carbon cycle science
Potential Users:  Researchers, local stakeholders
Stakeholders:  
Current Application Readiness Level:  4
Start Application Readiness Level:  2
Target Application Readiness Level:  4
Future Developments:  
Limitations:  Difficult to extend to other region or time period because of InSAR data access policy
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Map of phase-height and biomass change
Time Period:  2011-2016
Description:  
Status:  Public
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Forest degradation, forest structure, aboveground biomass, InSar
Spatial Extent:  Tapajos Forest, Para, Brazil
Spatial Resolution:  50 m to 250 m
Temporal Frequency:  Annual
Input Data Products:  InSAR TanDEM-x Spaceborne Interferometer, LiDAR, and field measurements
Algorithm/Models Used:  
Evaluation:  Field measurements
Intercomparison Efforts/Gaps:  Comparison with field data
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  Research
Relevant Policies/Programs:  Carbon monitoring, carbon cycle science
Potential Users:  Researchers
Stakeholders:  
Current Application Readiness Level:  4
Start Application Readiness Level:  2
Target Application Readiness Level:  4
Future Developments:  
Limitations:  Difficult to extend to other region or time period because of InSAR data access policy
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Aboveground Biomass Change for Amazon Basin, Mexico, and Pantropical Belt, 2003-2016
Start Date:  01/2003      End Date:  12/2016     (2003 through 2016)
Description:  This dataset provides gridded estimates of aboveground biomass (AGB) for live dry woody vegetation density in the form of both stock for the baseline year 2003 and annual change in stock from 2003 to 2016. Data are at a spatial resolution of approximately 500 m (463.31 m; 21.47 ha) for three geographies: the biogeographical limit of the Amazon Basin, the country of Mexico, and a Pantropical belt from 40 degrees North to 30 degrees South latitudes. Estimates were derived from a multi-step modeling approach that combined field measurements with co-located LiDAR data from NASA ICESat Geoscience Laser Altimeter System (GLAS) to calibrate a machine-learning (ML) algorithm that generated spatially explicit annual estimates of AGB density. ML inputs included a suite of satellite and ancillary spatial predictor variables compiled as wall-to-wall raster mosaics, including MODIS products, WorldClim climate variables reflecting current (1960-1990) climatic conditions, and SoilGrids soil variables. The 14-year time series was analyzed at the grid cell (~500 m) level with a change point-fitting algorithm to quantify annual losses and gains in AGB. Estimates of AGB and change can be used to derive total losses, gains, and the net change in aboveground carbon density over the study period as well as annual estimates of carbon stock.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  Mexico, Amazon Basin, Pantropics
Spatial Resolution:  variable ~500 m (463.31 m; 21.47 ha)
Temporal Frequency:  Annual
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1824
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1824
Archived Data Citation:  Baccini, A., W. Walker, L.E. Carvalho, M.K. Farina, K.K. Solvik, and D. Sulla-Menashe. 2021. Aboveground Biomass Change for Amazon Basin, Mexico, and Pantropical Belt, 2003-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1824

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:40.00000 South Latitude:-30.00000

 
Publications: Baccini, A., Walker, W., Carvalho, L., Farina, M., Sulla-Menashe, D., Houghton, R. A. 2017. Tropical forests are a net carbon source based on aboveground measurements of gain and loss. Science. 358(6360), 230-234. DOI: 10.1126/science.aam5962

Treuhaft, R., Lei, Y., Goncalves, F., Keller, M., Santos, J., Neumann, M., Almeida, A. 2017. Tropical-Forest Structure and Biomass Dynamics from TanDEM-X Radar Interferometry. Forests. 8(8), 277. DOI: 10.3390/f8080277

Walker, W. S., Gorelik, S. R., Baccini, A., Aragon-Osejo, J. L., Josse, C., Meyer, C., Macedo, M. N., Augusto, C., Rios, S., Katan, T., de Souza, A. A., Cuellar, S., Llanos, A., Zager, I., Mirabal, G. D., Solvik, K. K., Farina, M. K., Moutinho, P., Schwartzman, S. 2020. The role of forest conversion, degradation, and disturbance in the carbon dynamics of Amazon indigenous territories and protected areas. Proceedings of the National Academy of Sciences. 117(6), 3015-3025. DOI: 10.1073/pnas.1913321117

Wang, J. A., Baccini, A., Farina, M., Randerson, J. T., Friedl, M. A. 2021. Disturbance suppresses the aboveground carbon sink in North American boreal forests. Nature Climate Change. 11(5), 435-441. DOI: 10.1038/s41558-021-01027-4

Wigneron, J., Fan, L., Ciais, P., Bastos, A., Brandt, M., Chave, J., Saatchi, S., Baccini, A., Fensholt, R. 2020. Tropical forests did not recover from the strong 2015-2016 El Nino event. Science Advances. 6(6). DOI: 10.1126/sciadv.aay4603

Archived Data Citations: Baccini, A., W. Walker, L.E. Carvalho, M.K. Farina, K.K. Solvik, and D. Sulla-Menashe. 2021. Aboveground Biomass Change for Amazon Basin, Mexico, and Pantropical Belt, 2003-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1824


 

Cochrane (CMS 2015) (2016)
Project Title:Continuation and expansion to a national-scale of the filling a critical gap in Indonesia's national carbon monitoring, reporting, and verification capabilities for supporting REDD+ activities: Incorporating, quantifying and locating fire emissions from within tropical peat-swamp forests project

Science Team
Members:

Mark Cochrane, University of Maryland (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2015)
Precursor Projects: Cochrane (CMS 2013)  
Successor Projects: Cochrane (CMS 2018)  
Abstract: Indonesia ranks as the 3rd largest CO2eq emitting nation, largely due to episodic uncontrolled fires within drained peat-swamp forests. The original project (NNX13AP46G) set out to 1) provide extensive field investigation of land cover, hydrologic, fuel and fire dynamics in a 120,000 ha REDD+ project in Central Kalimantan; 2) Collect a new LIDAR dataset to complement our existing 2007 and 2011 coverages; 3) Conduct groundbreaking detailed emissions field sampling of smoldering in-situ peat fires; and 4) Generate a fully parameterized and validated annual emissions model for the study region in support of its REDD+ project. Despite extensive bureaucratic and logistical challenges and delays inherent in working in Indonesia, objectives 1-3 have now been completed and the modeling efforts are ongoing with all necessary data now in hand as we complete the original project time period. However, our recent unprecedented emission findings (Stockwell et al. 2016), gained in situ during the height of the 2015 El Niño, have documented substantial differences between the actual regional peat fire emissions and existing emission factors, indicating regional Indonesian carbon equivalent emissions (100 year) may have been 19% less than current IPCC-based emission factor estimates. The IPCC emission factors are derived from one lab study burning peat from Sumatra (Christian et al. 2003) and considerable variation in emissions may exist between peat fires of Indonesia’s three major peat formations highlighting the need for the additional field emissions measurements we intend to carry out in the continuation of the project proposed here. We propose expanding to a national level, our successful regional (Kalimantan) CMS project (NNX13AP46G), to better advance Indonesia’s Monitoring, Reporting and Verification (MRV) capabilities for peatland carbon emissions and support nationwide Reducing Emissions from Deforestation and Forest Degradation (REDD) efforts. We will implement our standardized field-based analyses of fuels, hydrology, peat burning characteristics and fire emissions, developed from our ongoing work in a 120,000 ha REDD+ project, to regionally parameterize our peatland emissions model for all of Indonesia’s major peatland areas by including three new locations, Riau and Jambi (Sumatra) and Western Papua (Papua), for inclusion within the Indonesian National Carbon Accounting System (INCAS). We will conduct on-site whole air sampling of natural peat smoke plumes in situ for precise measurement of non-reactive greenhouse gases, collect peat samples just in front of these active peat fires, and burn the samples in the US while measuring aerosol mass and optical properties and reactive gases. This will create comprehensive and pertinent emissions factors (EFs) for each study region that will be critically important for assessing health impacts and total global warming potential (GWP) of these emissions. Remotely sensed land cover/change (Landsat) and surface fire ignition timing and locations (MODIS) provide spatial and temporal drivers for the modeled emissions that will now be validated/constrained at a national level using biomass burning emissions estimations derived from Visible/Infrared Imager and Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (NPP) satellite and the new Japanese Geostationary Meteorological Satellite (Himawari-8). Multiple LIDAR datasets (2014, 2011, 2007) for Kalimantan are being used to quantify model accuracy, and new work will be undertaken to quantify uncertainty in our most recent LIDAR-based digital terrain model (DTM), further improving assessments of modeling errors.
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • MRV

Participants:

Israr Albar, Indonesia Ministry of Environment and Forestry
Grahame Applegate, University of the Sunshine Coast
Mark Cochrane, University of Maryland
Ati Dwi Nurhayati, Bogor Agricultural University
Laura Graham, South Dakota State University
Stephen (Steve) Hagen, Applied Geosolutions
Erianto (Indra) Putra, South Dakota State University
Asmadi Saad, Jambi University
Bambang Saharjo, Bogor Agricultural University
Yenni Vetrita, South Dakota State University
Bob Yokelson, University of Montana
Xiaoyang Zhang, South Dakota State University

Project URL(s): None provided.
 
Data
Products:
Product Title:  Daily biomass combustion map
Time Period:  2016 - 2018
Description:  Daily biomass combustion in a 0.5-degree grid across the Indonesia from 2016-2018
Status:  Planned
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Indonesia
Spatial Resolution:  
Temporal Frequency:  Daily
Input Data Products:  Global Fire Emission Database (GFED3.1), Global Fire Assimilation System (GFAS), Quick Fire Emissions Data (QFED), Fire Inventory from NCAR (FINN), Global Biomass Burning Emission Product from Geostationary satellites (GBBEP-Geo), VIIRS, Himawari 8/9
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  MRV, REDD+, Fire Management, GHG emissions inventory, Forest inventory, Land management, Air quality protection
Relevant Policies/Programs:  REDD+, National Peatland Restoration Program, National Emission Reduction Program 
Potential Users:  Ministry of Environment and Forestry, GOI; Peatland Restoration Agency (BRG); Local Governments; LAPAN
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Daily fire emission map
Time Period:  2016 - 2018
Description:  Daily fire emissions (CO, PM2.5, and PM10) a 0.5-degree grid across the Indonesia from 2016-2018
Status:  Planned
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Indonesia
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  Global Fire Emission Database (GFED3.1), Global Fire Assimilation System (GFAS), Quick Fire Emissions Data (QFED), Fire Inventory from NCAR (FINN), Global Biomass Burning Emission Product from Geostationary satellites (GBBEP-Geo), VIIRS, Himawari 8/9
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  MRV, REDD+, Fire Management, GHG emissions inventory, Forest inventory, Land management, Air quality protection
Relevant Policies/Programs:  REDD+, National Peatland Restoration Program, National Emission Reduction Program 
Potential Users:  Ministry of Environment and Forestry, GOI; Peatland Restoration Agency (BRG); Local Governments; LAPAN; IPCC
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Estimates regional and national peat-fire related emissions  
Description:  Create an MRV system that quantifies fire emissions on regional and national-scale in tropical peat-swamp forests for inventory and land management purposes
Status:  Preliminary
CMS Science Theme(s):  Decision Support; Land Biomass; Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Central Kalimantan, Riau, Jambi, and West Papua Provinces, Indonesia
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  TRMM/GPM, Airborne LiDAR, Terra/Aqua MODIS, Landsat 5, 7 & 8
Algorithm/Models Used:  Under development
Evaluation:  Has been done for Central Kalimantan; will extend to Riau, Jambi and West Papua Provinces
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  MRV, REDD+, Fire Management, GHG emissions inventory, Forest inventory, Land management, Air quality protection
Relevant Policies/Programs:  REDD+, National Peatland Restoration Program, National Emission Reduction Program
Potential Users:  Ministry of Environment and Forestry, GOI; Peatland Restoration Agency (BRG); Local Governments; LAPAN; IPCC; Ministry of Health
Stakeholders:  CIMTROP, Palangkaraya University (Point of Contact: Dr. Nina Yulianti, ninayulianti.unpar@gmail.com); Forest Fire Laboratory, Silviculture Department, Faculty of Forestry, Bogor Agricultural University (Point of Contact: Ati Nurhayati, awinur@yahoo.com)
Current Application Readiness Level:  6
Start Application Readiness Level:  5
Target Application Readiness Level:  8
Future Developments:  Send canisters from USA to sample the smoke from peat fires in four research areas: Central Kalimantan, Riau, Jambi, and West Papua Provinces
Limitations:  May not detect seasonal variability and thus may underestimate emissions
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Fire emission algorithm
Time Period:  2016 - 2019
Description:  Algorithm to estimate fire emissions from both polar orbiting and geostationary satellite observations
Status:  Planned
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Indonesia
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  Global Fire Emission Database (GFED3.1), Global Fire Assimilation System (GFAS), Quick Fire Emissions Data (QFED), Fire Inventory from NCAR (FINN), Global Biomass Burning Emission Product from Geostationary satellites (GBBEP-Geo), VIIRS, Himawari 8/9
Algorithm/Models Used:  Under development
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  MRV, REDD+, Fire Management, GHG emissions inventory, Forest inventory, Land management, Air quality protection
Relevant Policies/Programs:  REDD+, National Peatland Restoration Program, National Emission Reduction Program 
Potential Users:  Ministry of Environment and Forestry, GOI; LAPAN; IPCC
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Peat Fire Scene Evaluation Method
Time Period:  2016 - 2019 
Description:  Create an appropriate method to evaluate peat fire occurrences, its causes and impacts
Status:  Preliminary
CMS Science Theme(s):  Decision Support; Land Biomass; Land-Atmosphere Flux
Keywords:  Evaluation: observations
Spatial Extent:  Central Kalimantan, Riau, Jambi, and West Papua Provinces, Indonesia
Spatial Resolution:  
Temporal Frequency:  Seasonally
Input Data Products:  TRMM/GPM, Airborne LiDAR, Terra/Aqua MODIS, Landsat 5, 7 & 8
Algorithm/Models Used:  
Evaluation:  Work in progress; extending to national scale
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  MRV, REDD+, Fire Management, GHG emissions inventory, Forest inventory, Land management, Air quality protection
Relevant Policies/Programs:  REDD+, National Peatland Restoration Program, National Emission Reduction Program 
Potential Users:  Ministry of Environment and Forestry, GOI; Peatland Restoration Agency (BRG); Local Governments; Estate Crops and Plantations; Ministry of Agriculture
Stakeholders:  Center of Disaster Research, Riau University (Point of Contact: Dr. Adhi Prayitno (gendon_tho@yahoo.co.uk)); CIMTROP, Palangkaraya University (Point of Contact: Dr. Nina Yulianti, ninayulianti.unpar@gmail.com); Directorate of Forest Fire Management, DG of Climate Change, Ministry of Environment and Forestry, GOI (Point of Contact: Dr. Israr Albar, israralbar@gmail.com); Forest Fire Laboratory, Silviculture Department, Faculty of Forestry, Bogor Agricultural University (Point of Contact: Ati Nurhayati, awinur@yahoo.com)
Current Application Readiness Level:  6
Start Application Readiness Level:  5
Target Application Readiness Level:  8
Future Developments:  Apply the FSE Methods in the new research areas: Riau, Jambi and West Papua Provinces; Conduct the FSE Methods during peak peat fire season in dry season
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Annual Burned Area from Landsat, Mawas, Central Kalimantan, Indonesia, 1997-2015
Start Date:  01/1997      End Date:  12/2015     (2016 - 2019 )
Description:  This dataset provides maps of annual burned area for the part of Mawas conservation program in Central Kalimantan, Indonesia from 1997 through 2015. Landsat imagery (TM, ETM+, OLI/TIR) at 30 m resolution was obtained for this 19-year period, including the variables surface reflectance, brightness temperature, and pixel quality assurance, plus the indices NDVI, NDMI, NBR, NBR2, SAVI, and MSAVI. The MODIS active fire product (MCD14) was used to define when fires occurred. Random Forest classifications were used to separate burned and unburned 30-m pixels with inputs of composites of Landsat indices and thermal bands, based on the pre- and post-fire values.
Status:  Archived
CMS Science Theme(s):  Decision Support; Land Biomass; Land-Atmosphere Flux
Keywords:  Disturbance: severity
Spatial Extent:  Mawas area, Central Kalimantan, Indonesia
Spatial Resolution:  30 m
Temporal Frequency:  Annually
Input Data Products:  SPOT-5, MODIS active fire, TRMM/GPM, Airborne LiDAR, Terra/Aqua MODIS, Landsat 5, 7 & 8
Algorithm/Models Used:  MODIS monthly BA-products (MCD45A1 and MCD64A1)
Evaluation:  Work in progress
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  MRV, REDD+, Fire Management, GHG emissions inventory, Forest inventory, Land management, Air quality protection
Relevant Policies/Programs:  REDD+, National Peatland Restoration Program, National Peatland Mapping, National Emission Reduction Program
Potential Users:  Ministry of Environment and Forestry, GOI; Peatland Restoration Agency (BRG); Local Governments; LAPAN; IPCC
Stakeholders:  CIMTROP, Palangkaraya University (Point of Contact: Dr. Nina Yulianti, ninayulianti.unpar@gmail.com); Directorate of Forest Fire Management, DG of Climate Change, Ministry of Environment and Forestry, GOI (Point of Contact: Dr. Israr Albar, israralbar@gmail.com); Forest Fire Laboratory, Silviculture Department, Faculty of Forestry, Bogor Agricultural University (Point of Contact: Ati Nurhayati, awinur@yahoo.com)
Current Application Readiness Level:  6
Start Application Readiness Level:  3
Target Application Readiness Level:  7
Future Developments:  Accuracy improvement
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1708
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1708
Archived Data Citation:  Vetrita, Y., and M.A. Cochrane. 2019. Annual Burned Area from Landsat, Mawas, Central Kalimantan, Indonesia, 1997-2015. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1708

Bounding Coordinates:
West Longitude:114.39000 East Longitude:114.61000
North Latitude:-2.21000 South Latitude:-2.50000

Product Title:  Land Use and Cover Maps from Landsat, Mawas, Central Kalimantan, Indonesia, 1994-2019
Start Date:  01/1994      End Date:  12/2019     (Every fifth year, for the period 1994–2019)
Description:  This dataset contains annual land use/cover (LUC) maps at 30 m resolution across Mawas, Central Kalimantan, Indonesia. There are six files, each representing a five-year interval over the period 1994-2019. An additional file for 2015 was created for accuracy assessment. A high-quality and low-cloud coverage image from Landsat 5 or Landsat 8 over each 5-year period was selected or composited for the January-August timeframe. Investigators used their knowledge to manually identify training polygons in these images for five LUC classes: peat swamp forest, tall shrubs/ secondary forest, low shrubs/ferns/grass, urban/bare land/open flooded areas, and river. Pixel values of Landsat Tier 1 surface reflectance products and selected indices were extracted for each LUC and used to predict LUC classes across the Mawas study area using the Classification and Regression Trees (CART) method. These data can be used to evaluate the relationship between fire occurrence and land cover type in the study site.
Status:  Archived
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  
Spatial Extent:  Central Kalimantan, Indonesia
Spatial Resolution:  30 m
Temporal Frequency:  Annual
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1838
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1838
Archived Data Citation:  Vetrita, Y., and M.A. Cochrane. 2021. Land Use and Cover Maps from Landsat, Mawas, Central Kalimantan, Indonesia, 1994-2019. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1838

Bounding Coordinates:
West Longitude:114.36000 East Longitude:114.65000
North Latitude:-2.16000 South Latitude:-2.56000

Product Title:  Fire Particulate Emissions from Combined VIIRS and AHI Data for Indonesia, 2015-2020
Start Date:  07/2015      End Date:  12/2020     (2015-07-04 to 2020-12-31)
Description:  This dataset provides 10-minute fire emissions within 0.1-degree regularly spaced intervals across Indonesia from July 2015 to December 2020. The dataset was produced with a top-down approach based on fire radiative energy (FRE) and smoke aerosol emission coefficients (Ce) derived from multiple new-generation satellite observations. Specifically, the Ce values of peatland, tropical forest, cropland, or savanna and grassland were derived from fire radiative power (FRP) and emission rates of smoke aerosols based on Visible Infrared Imaging Radiometer Suite (VIIRS) active fire and aerosol products. FRE for each 0.1-degree interval was calculated from the diurnal FRP cycle that was reconstructed by fusing cloud-corrected FRP retrievals from the high temporal-resolution (10 mins) Himawari-8 Advanced Himawari Imager (AHI) with those from high spatial-resolution (375 m) VIIRS. This new dataset was named the Fused AHI-VIIRS based fire Emissions (FAVE). Fire emissions data are provided in comma-separated values (CSV) format with one file per month from July 2015 to December 2020. Each file includes variables of fire observation time, fire geographic location, classification, fire radiative energy, various fire emissions and related standard deviations.
Status:  Archived
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; MRV
Keywords:  Land Biomass, Land-Atmosphere Flux, MRV
Spatial Extent:  Indonesia
Spatial Resolution:  Point locations based on satellite observations at 375-m (VIIRS) / 2-km (AHI) resolution, organized within 0.1-degree regular intervals
Temporal Frequency:  10 minutes
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/2118
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/2118
Archived Data Citation:  Lu, X., X. Zhang, F. Li, and M.A. Cochrane. 2023. Fire Particulate Emissions from Combined VIIRS and AHI Data for Indonesia, 2015-2020. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/2118

Bounding Coordinates:
West Longitude:89.00000 East Longitude:153.00000
North Latitude:10.10000 South Latitude:-11.00000

 
Publications: Applegate, Grahame, Laura L. B. Graham, Andri Thomas, Ahmad Yunan, Didie, Agus, Ato, Bambang H. Saharjo and Mark A. Cochrane. 2017.Fire Scene Evaluation Field Manual/ Petunjuk laPang evaluasi kejadian kebakaran Penerbit. IPB Press IPB Science Techno Park, Kota Bogor - Indonesia ISBN: 978-602-440-173-3

Goldstein, J. E., Graham, L., Ansori, S., Vetrita, Y., Thomas, A., Applegate, G., Vayda, A. P., Saharjo, B. H., Cochrane, M. A. 2020. Beyond slash-and-burn: The roles of human activities, altered hydrology and fuels in peat fires in Central Kalimantan, Indonesia. Singapore Journal of Tropical Geography. 41(2), 190-208. DOI: 10.1111/sjtg.12319

Jayarathne, T., Stockwell, C. E., Gilbert, A. A., Daugherty, K., Cochrane, M. A., Ryan, K. C., Putra, E. I., Saharjo, B. H., Nurhayati, A. D., Albar, I., Yokelson, R. J., Stone, E. A. 2018. Chemical characterization of fine particulate matter emitted by peat fires in Central Kalimantan, Indonesia, during the 2015 El Nino. Atmospheric Chemistry and Physics. 18(4), 2585-2600. DOI: 10.5194/acp-18-2585-2018

Kemal Putra, I., Hero Saharjo, B., Wasis, B. 2019. Institutional Challenge on Forest and Land Fire Management at the Site Level. Jurnal Ilmu Pertanian Indonesia. 24(2), 151-159. DOI: 10.18343/jipi.24.2.151

Li, F., Zhang, X., Kondragunta, S., Lu, X. 2020. An evaluation of advanced baseline imager fire radiative power based wildfire emissions using carbon monoxide observed by the Tropospheric Monitoring Instrument across the conterminous United States. Environmental Research Letters. 15(9), 094049. DOI: 10.1088/1748-9326/ab9d3a

Lu, X., Zhang, X., Li, F., Cochrane, M. A. 2019. Investigating Smoke Aerosol Emission Coefficients Using MODIS Active Fire and Aerosol Products: A Case Study in the CONUS and Indonesia. Journal of Geophysical Research: Biogeosciences. 124(6), 1413-1429. DOI: 10.1029/2018JG004974

Putra, E. I., Cochrane, M. A., Vetrita, Y., Graham, L., Saharjo, B. H. 2018. Determining critical groundwater level to prevent degraded peatland from severe peat fire. IOP Conference Series: Earth and Environmental Science. 149, 012027. DOI: 10.1088/1755-1315/149/1/012027

Sinclair, A. L., Graham, L. L., Putra, E. I., Saharjo, B. H., Applegate, G., Grover, S. P., Cochrane, M. A. 2020. Effects of distance from canal and degradation history on peat bulk density in a degraded tropical peatland. Science of The Total Environment. 699, 134199. DOI: 10.1016/j.scitotenv.2019.134199

Vetrita, Y., Cochrane, M. A. 2019. Fire Frequency and Related Land-Use and Land-Cover Changes in Indonesia's Peatlands. Remote Sensing. 12(1), 5. DOI: 10.3390/rs12010005

Yokelson, R. J., Saharjo, B. H., Stockwell, C. E., Putra, E. I., Jayarathne, T., Akbar, A., Albar, I., Blake, D. R., Graham, L. L. B., Kurniawan, A., Meinardi, S., Ningrum, D., Nurhayati, A. D., Saad, A., Sakuntaladewi, N., Setianto, E., Simpson, I. J., Stone, E. A., Sutikno, S., Thomas, A., Ryan, K. C., Cochrane, M. A. 2022. Tropical peat fire emissions: 2019 field measurements in Sumatra and Borneo and synthesis with previous studies. Atmospheric Chemistry and Physics. 22(15), 10173-10194. DOI: 10.5194/acp-22-10173-2022

Zarzana, K. J., Selimovic, V., Koss, A. R., Sekimoto, K., Coggon, M. M., Yuan, B., Dube, W. P., Yokelson, R. J., Warneke, C., de Gouw, J. A., Roberts, J. M., Brown, S. S. Primary emissions of glyoxal and methylglyoxal from laboratory measurements of open biomass burning DOI: 10.5194/acp-2018-521

Archived Data Citations: Vetrita, Y., and M.A. Cochrane. 2019. Annual Burned Area from Landsat, Mawas, Central Kalimantan, Indonesia, 1997-2015. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1708

Vetrita, Y., and M.A. Cochrane. 2021. Land Use and Cover Maps from Landsat, Mawas, Central Kalimantan, Indonesia, 1994-2019. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1838

Lu, X., X. Zhang, F. Li, and M.A. Cochrane. 2023. Fire Particulate Emissions from Combined VIIRS and AHI Data for Indonesia, 2015-2020. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/2118


 

Cook (CMS 2015) (2016)
Project Title:Remote Sensing as a Bridge to Operational Forest Carbon Monitoring in Interior Alaska

Science Team
Members:

Bruce Cook, NASA GSFC (Project Lead)
Hans Andersen, U.S. Forest Service Pacific Northwest Research Station

Solicitation:NASA: Carbon Monitoring System (2015)
Precursor Projects: Cook (TE 2014)   Morton (CMS 2013)  
Successor Projects: Cook (CMS 2018)  
Abstract: Monitoring U.S. forest carbon stocks is critical for natural resource management and national greenhouse gas reporting activities. The USFS Forest Inventory and Analysis (FIA) program—the largest network of permanent forest inventory plots in the world covers most U.S. forestlands. However, more than 450,000 km2 of forests in Interior Alaska (15% of US forestland) are not included in the FIA program, as these remote regions are difficult and expensive to monitor with standard field methods. Recent warming and projected future impacts from climate change on forest carbon stocks, composition, and extent have elevated the need to develop new approaches for forest monitoring in Alaska. The broader policy focus on land carbon sinks also encourages monitoring and accounting of the complete US land carbon sink, including Interior Alaska. Article 4 of the Paris Agreement recognizes the importance of “removals by sinks of greenhouse gases,” and specifically requests that national inventories include information on removals. Here, we propose to expand the joint NASA-USFS Pilot Project in the Tanana Inventory Unit, funded in part by ROSES-2013 CMS, to inventory a second USFS region in Interior Alaska, the Susitna-Copper River (SCR) Inventory Unit. Based on the success of the pilot project, the USFS has initiated a 10-year, $25M inventory plan for Interior Alaska using remote sensing data from Goddard’s Lidar, Hyperspectral, and Thermal (G-LiHT) Airborne Imager (http://gliht.gsfc.nasa.gov). The proposed research leverages USFS funding for G-LiHT data collection. However, the USFS inventory activity does not support research collaboration between NASA and USFS scientists, data analysis, or methods development. The proposed CMS project supports the transition of lidar- assisted forest inventory activities from research to operations, targeting specific objectives for NASA’s CMS program to use “remote sensing data products to produce and evaluate prototype MRV system approaches” and “studies that address research needs to advance remote sensing-based approaches to MRV” identified in Section 2.1 of the ROSES-2015 CMS solicitation (A.7). The proposed project has five components. The first three activities represent a continuation of research themes and data products outlined in the NASA-USFS Pilot Project, including specific requests for core inventory products by the USFS Forest Inventory & Analysis (FIA) Program, a key stakeholder for this effort. Core project components include 1) collaboration between USFS and NASA scientists on experimental design for optimal integration of field and lidar data for forest carbon monitoring, 2) estimation of forest carbon stocks for the SCR Inventory Unit using established methods to combine plot and lidar data, and 3) development of new, spatially explicit estimates of carbon stocks and uncertainties using hierarchical Bayesian statistical methods. In addition to these core inventory activities, we will use the combination of field inventory plots and G-LiHT data to 4) develop estimates of woody shrub biomass (e.g., alder and willow), a dominant feature of boreal forest landscapes that are not included in FIA inventory estimates, and 5) collaborate with USFS Forest Health experts to identify mortality and carbon losses from insects and disease (e.g., spruce bark beetle, aspen and birch leaf miners, birch leaf roller, alder dieback and canker disease). These additional project components target two specific needs identified by USFS scientists and stakeholders. The main outcomes from this work will be estimates of total (live + dead) forest carbon stocks, including woody shrubs, and associated uncertainties for the SCR Inventory Unit of Interior Alaska. These estimates provide critical and timely information for carbon monitoring and resource management, and baseline conditions for the spatial distribution of vegetation carbon stocks in a region undergoing rapid climate change.
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • MRV

Participants:

Michael Alonzo, American University
Hans Andersen, U.S. Forest Service Pacific Northwest Research Station
Chad Babcock, University of Minnesota
Bruce Cook, NASA GSFC
Andrew (Andy) Finley, Michigan State University
John Lundquist, USDA Forest Service
Douglas (Doug) Morton, NASA GSFC
Robert Pattison, USDA Forest Service, Anchorage Forestry Sciences Laboratory
Beth Schultz, USDA Forest Service

Project URL(s): None provided.
 
Data
Products:
Product Title:  Total forest carbon stocksfor the Susitna-Copper River Inventory Unit of Interior Alaska
Start Date:  06/2018      End Date:  09/2019     (2018 airborne campaign, 2018-2019 ground plot sampling)
Description:  Estimates of total (live + dead) forest carbon stocks, including woody shrubs, and associated uncertainties for the Susitna-Copper River Inventory Unit of Interior Alaska. These estimates provide critical and timely information for carbon monitoring and resource management, and baseline conditions for the spatial distribution of vegetation carbon stocks in a region undergoing rapid climate change.
Status:  Preliminary
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Forest carbon stocks; forest extent; forest cover; forest/non-forest; canopy height; digital elevation model; forest type; woody shrubs; forest health; uncertainties; G-LiHT mult-sensor airborne image data; lidar; hyperspectra;
Spatial Extent:  
Spatial Resolution:  30 meter
Temporal Frequency:  baseline data point for USDA FIA
Input Data Products:  NASA Goddard's Lidar, Hyperspectral and Thermal airborne imagery; USDA Forest Service FIA plot measurements; ; Landsat-derived land cover classification (e.g., NLCD) and forest cover co-variates (e.g., Hansen et al., Global Forest Change)
Algorithm/Models Used:  The data product was developed using a hierarchical spatial Bayesian model that accommodates sparsely sampled forest inventory plot data and LiDAR to deliver wall-to-wall predictions with associated probabilistic uncertainty quantification (Finley et al. 2014); see https://glihtdata.gsfc.nasa.gov/tanana.html
Evaluation:  USDA Forest Inventory and Analysis ground plots provide data for creating and evaluating model performance.
Intercomparison Efforts/Gaps:  Intercomparisons have been made between Design-Based Model-Assisted (DBMA) and geostatistical Model-Based (MB) approaches, i.e., wall-to-wall estimates that leverage lidar and auxiliary information to improve estimates of total forest biomass, and the traditional Design-Based (DB) approach represents the standard Forest Inventory and Analysis (FIA) program estimation procedure using field observations alone.
Uncertainty Estimates:  Design-Based, Design-Based Model-Assisted (DBMA), Model-Based (MB) uncertainties are computed for the region. Spatial biomass maps draw on the pixel-level posterior predictive distribution samples to provide full statistical inference (i.e., point and interval estimates). Model predictions at the ground plots, and along- and adjacent-to G-LiHT transects generally show improved spatial resolution and the standard deviation of prediction is smaller (see https://glihtdata.gsfc.nasa.gov/tanana.html)
Uncertainty Categories:  Design-Based, Design-Based Model-Assisted (DBMA), Model-Based (MB) uncertainties are computed for the region.
Application Areas:  Remote regions of the world that are difficult and expensive to monitor with standard field methods.
Relevant Policies/Programs:  USDA Forest Service Forest Inventory and Analysis (FIA) program; Monitoring, Reporting, and Verification (MRV) of US forest carbon stocks and National Greenhouse Gas Inventory reporting of emissions from the forest sector (Woodall et al. 2015)
Potential Users:  USDA Forest Service; National Park Service; Alaska Department of Natural Resources, Division of Forestry; US Fish & Wildlife Service; US Geological Survey; US Dept of Interior, Bureau of Land Management
Stakeholders:  USFS (Point of Contact: Hans Eric Andersen)
Current Application Readiness Level:  8
Start Application Readiness Level:  7
Target Application Readiness Level:  9
Future Developments:  In additional to extending estimates to other inventory units in interior AK over the next 10 years, we plan to 1) derive more inventory variables directly from G-LiHT data, therby avoid sampling bias from remote or wilderness areas that cannot be accessed by FIA crews; benchmark shrub biomass and distribution, since the FIA inventory does not include shrub species (e.g., willow, alder), which are critical for complete carbon monitoring in this rapidly-warming landscape; and 3) map the distribution of soil organic carbon based on soil cores from FIA plots and covariates derived from G-LiHT and other remote sensing data.
Limitations:  Density of ground and airborne transects, and uncertainties associated with covariates used in geostatistical models.
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
Data Server URL(s):

http://gliht.gsfc.nasa.gov
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-153.00000 East Longitude:-141.00000
North Latitude:63.00000 South Latitude:61.00000

 
Publications: Alonzo, M., Andersen, H., Morton, D., Cook, B. 2018. Quantifying Boreal Forest Structure and Composition Using UAV Structure from Motion. Forests. 9(3), 119. DOI: 10.3390/f9030119

Alonzo, M., Dial, R. J., Schulz, B. K., Andersen, H., Lewis-Clark, E., Cook, B. D., Morton, D. C. 2020. Mapping tall shrub biomass in Alaska at landscape scale using structure-from-motion photogrammetry and lidar. Remote Sensing of Environment. 245, 111841. DOI: 10.1016/j.rse.2020.111841

Alonzo, M., Morton, D. C., Cook, B. D., Andersen, H., Babcock, C., Pattison, R. 2017. Patterns of canopy and surface layer consumption in a boreal forest fire from repeat airborne lidar. Environmental Research Letters. 12(6), 065004. DOI: 10.1088/1748-9326/aa6ade

Andersen, H. -E., C. Babcock, B. Cook, D. Morton, A. Finley and M. Alonzo. Using remote sensing to support forest inventory in interior Alaska – demonstration of a generalized regression estimator in a two-phase, model-assisted sampling design using two-sources of auxiliary data. Forests (submitted).

Babcock, C., Finley, A. O., Andersen, H., Pattison, R., Cook, B. D., Morton, D. C., Alonzo, M., Nelson, R., Gregoire, T., Ene, L., Gobakken, T., Naesset, E. 2018. Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations. Remote Sensing of Environment. 212, 212-230. DOI: 10.1016/j.rse.2018.04.044

Babcock, C., Finley, A. O., Cook, B. D., Weiskittel, A., Woodall, C. W. 2016. Modeling forest biomass and growth: Coupling long-term inventory and LiDAR data. Remote Sensing of Environment. 182, 1-12. DOI: 10.1016/j.rse.2016.04.014

Ene, L. T., Gobakken, T., Andersen, H., Naesset, E., Cook, B. D., Morton, D. C., Babcock, C., Nelson, R. 2018. Large-area hybrid estimation of aboveground biomass in interior Alaska using airborne laser scanning data. Remote Sensing of Environment. 204, 741-755. DOI: 10.1016/j.rse.2017.09.027

Finley, A. O., Datta, A., Cook, B. D., Morton, D. C., Andersen, H. E., Banerjee, S. 2019. Efficient Algorithms for Bayesian Nearest Neighbor Gaussian Processes. Journal of Computational and Graphical Statistics. 28(2), 401-414. DOI: 10.1080/10618600.2018.1537924

Finley, A. O., S. Banerjee, Y. Zhou and B. D. Cook. 2016. Process-based hierarchical models for coupling high-dimensional LiDAR and forest variables over large geographic domains. Journal of the American Statistical Association, arXiv: 1603.07409

Montesano, P. M., Neigh, C. S., Wagner, W., Wooten, M., Cook, B. D. 2019. Boreal canopy surfaces from spaceborne stereogrammetry. Remote Sensing of Environment. 225, 148-159. DOI: 10.1016/j.rse.2019.02.012

Pattison, R., Andersen, H., Gray, A., Schulz, B., Smith, R. J., Jovan, S. 2018. Forests of the Tanana Valley State Forest and Tetlin National Wildlife Refuge, Alaska: results of the 2014 pilot inventory DOI: 10.2737/pnw-gtr-967

Shirota, S., A. O. Finley, B. D. Cook and S. Banerjee. Conjugate nearest neighbor Gaussian process models for efficient statistical interpolation of large spatial data. IEEE Transactions on Geoscience and Remote Sensing (submitted).

Shoot, C., H. -E. Andersen, Monika Moskal, C. Babcock, B. Cook and D. Morton. Classifying Forest Type in the National Forest Inventory Context from a Fusion of Hyperspectral and Lidar Data. Remote Sensing of Environment (submitted).

Taylor-Rodriguez, D., Finley, A. O., Datta, A., Babcock, C., Andersen, H., Cook, B. D., Morton, D. C., Banerjee, S. 2019. Spatial Factor Models for High-Dimensional and Large Spatial Data: An Application in Forest Variable Mapping. Statistica Sinica. DOI: 10.5705/ss.202018.0005

Finley, A. O., Banerjee, S., Zhou, Y., Cook, B. D., Babcock, C. 2017. Joint hierarchical models for sparsely sampled high-dimensional LiDAR and forest variables. Remote Sensing of Environment. 190, 149-161. DOI: 10.1016/j.rse.2016.12.004

Datta, A., Banerjee, S., Finley, A. O., Gelfand, A. E. 2016. On nearest-neighbor Gaussian process models for massive spatial data. WIREs Computational Statistics. 8(5), 162-171. DOI: 10.1002/wics.1383

Salazar, E., Hammerling, D., Wang, X., Sanso, B., Finley, A. O., Mearns, L. O. 2016. Observation-based blended projections from ensembles of regional climate models. Climatic Change. 138(1-2), 55-69. DOI: 10.1007/s10584-016-1722-1


 

Duren (CMS 2015) (2016)
Project Title:Prototype methane monitoring system for California

Science Team
Members:

Riley Duren, Carbon Mapper/U. Arizona (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2015)
Successor Projects: Duren (CMS 2018)  
Abstract: We propose to leverage a planned project with California stakeholder agencies to develop a prototype methane monitoring system for the state. The California Air Resources Board (CARB) and the California Energy Commission (CEC) are funding JPL to conduct a baseline survey of methane super-emitters across the state in late 2016 using proven airborne imaging spectrometers. The California Baseline Methane Survey will produce a data set of geolocated methane plume images for super-emitter sources. We propose to build on and dramatically improve the relevance of that data set by developing and validating point source flux estimates, uncertainty estimates, linking that information with multi-scale attribution data and regional flux estimates derived from other CMS and NACP projects (that employ satellite and surface observations), and coordinating with California stakeholder agencies to infuse those products into their decision-making frameworks. We will also work with a broader set of stakeholders to evaluate the potential future application of this Prototype Methane Monitoring System in other key regions in the US and internationally. Our proposed development of a Prototype Methane Monitoring System for California is of immediate societal relevance and significance given growing priorities to account for and mitigate methane emissions. The recently approved California law AB1496 states that “there is an urgent need to improve the monitoring and measurement of methane emissions from the major sources in California” and directs the California Air Resources Board to “undertake, in consultation with districts that monitor methane, monitoring and measurements of high-emission methane hot spots in the state using the best available and cost-effective scientific and technical methods”. Hence this project is directly responsive to that policy by addressing methane hot spots (super-emitters), by establishing a close collaboration between local, state, and US national stakeholders and by applying the best available scientific methods (including remote sensing derived point flux estimates and integration with other data sets across multiple spatial scales and emission sectors). The planned use for this data set by stakeholders spans multiple governance levels, emission sectors and programs – ranging from EPA Region 9’s interest in livestock emissions under the EPA AgStar program (the largest methane emission sector in California) to SC-AQMD’s focus on landfills, oil and gas (both for methane and potential co-emitted criteria pollutants). Similarly, the proposed end-to-end, multi-scale approach will also help explore and path-find the potential future extensibility of these methods to other regions in the US and internationally – addressing key US national priorities (US- Canada Joint Statement, 2016; President’s Climate Action Plan, 2013).
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Land-Atmosphere Flux
  • MRV

Participants:

Bart Croes, California Energy Commission / California Air Resources Board (retired) / CIRES at University of Colorado-Boulder
Riley Duren, Carbon Mapper/U. Arizona
Christian Frankenberg, Caltech
Abhinav Guha, Bay Area Air Quality Management District
Jorn Herner, California Air Resources Board
Francesca Hopkins, University of California Riverside
Daniel Jacob, Harvard University
Le (Elva) Kuai, JPL/Caltech
Ian Lloyd, Department of State
Trina Martynowicz, Environmental Protection Agency
Georgios Matheou, University of Connecticut
David Thompson, Jet Propulsion Laboratory / Caltech
Andrew Thorpe, JPL
Sanden Totten, 89.3 KPCC Southern California Public Radio

Project URL(s): None provided.
 
Data
Products:
Product Title:  Sources of Methane Emissions (Vista-LA), South Coast Air Basin, California, USA
Start Date:  01/2005      End Date:  03/2017
Description:  This data set provides spatial data products with identified and classified locations of potential methane (CH4) emitting facilities and infrastructure in the South Coast Air Basin (SoCAB). These data products form a GIS-based mapping database designed to address shortcomings in current urban CH4 source inventories and is known as Vista Los Angeles (Vista-LA). SoCAB is the air shed for the greater Los Angeles urban area, which includes urbanized portions of the Los Angeles, Orange, Riverside, and San Bernardino Counties, California, USA. Vista-LA consists of detailed spatial maps for facilities and infrastructure in the SoCAB that are known or expected sources of CH4 emissions and illustrates the spatial distribution of potential CH4 sources, representing a first step towards developing an urban-scale CH4 emissions gridded inventory for the SoCAB. Vista-LA spatial data sets were created utilizing an assortment of publicly available data sources from local, state, and federal agencies for the years 2012 to 2017. The final Vista-LA database contains over 33,000 entries, which are presented as thirteen CH4 emitting infrastructure maps.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux; MRV
Keywords:  Methane
Spatial Extent:  South Coast Air Basin (SoCAB), California, USA
Spatial Resolution:  point, polylines, and polygons
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  8
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  January 2018
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://daac.ornl.gov/NACP/guides/NACP_Vista_LA_CH4_Inventory.html
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1525
Archived Data Citation:  Carranza, V., T. Rafiq, I. Frausto-Vicencio, F. Hopkins, K.R. Verhulst, P. Rao, R.M. Duren, and C.E. Miller. 2018. Sources of Methane Emissions (Vista-LA), South Coast Air Basin, California, USA. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1525

Bounding Coordinates:
West Longitude:-118.91000 East Longitude:-116.68000
North Latitude:34.82000 South Latitude:33.43000

Product Title:  Full multi-scale methane portal
Description:  
Status:  Preliminary
CMS Science Theme(s):  Land-Atmosphere Flux; MRV
Keywords:  
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  California Air Resources Board (Point of Contact: Jorn Herner)
Current Application Readiness Level:  8
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):

https://methane.jpl.nasa.gov
Data Server URL(s):

https://methane.jpl.nasa.gov
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  California Methane Survey: quantitative plume image data
Description:  Quantitative methane plume mapping data products from the Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). The dataset consists of flightlines from the California Methane Survey obtained between 2016 and 2018. For each flightline, there are two associated files, the first is imaging spectrometer data with a filename suffix img. These are binary files representing the methane image data, with four channels: Radiance in visible red wavelengths, Radiance in visible green wavelengths, Radiance in visible blue wavelengths, and estimated CH4 enhancement above background, given in units of parts per million meters (ppm x m). The second file is a header file that provides META data, with a filename suffix img.hdr, ASCII human-readable header in ENVI format describes the specific dimensioning and layout of the flightline, and embeds geographic projection information.
Status:  On-going
CMS Science Theme(s):  Land-Atmosphere Flux; MRV
Keywords:  
Spatial Extent:  State of California
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  CARB, CEC, BA-AQMD, SC-AQMD, Southern California Gas, PG&E, Sunshine Canyon Landfill Local Enforcement Agency, Republic Services (landfill operator)
Stakeholders:  California Air Resources Board (Point of Contact: Jorn Herner); Debbie Gordon (Point of Contact: Rocky Mountain Institute)
Current Application Readiness Level:  8
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Methane Plumes Derived from AVIRIS-NG over Point Sources across California, 2016-2017
Start Date:  09/2016      End Date:  11/2017     (2016-2017)
Description:  This dataset provides maps of methane (CH4) plumes along flight lines over identified methane point-source emitting infrastructure across the State of California, USA collected during 2016 and 2017. Methane plume locations were derived from Next-Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG) overflights during the California Methane Survey. The survey was designed to cover at least 60% of the methane point source infrastructure in California guided by the Vista-CA dataset of identified locations of potential methane emitting facilities and infrastructure in three primary sectors (energy, agriculture, and waste). The purpose of the survey was to detect, quantify, and attribute point source emissions to specific infrastructure elements to improve the scientific understanding of regional methane budgets and to inform policy and planning activities that reduce methane emissions.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux; MRV
Keywords:  
Spatial Extent:  California USA
Spatial Resolution:  Flight lines were typically not on a formal grid pattern but focused on point-source features. Along a flight line, on average, AVIRIS-NG has a 1.8 km field of view and 3 m pixel resolution at typica
Temporal Frequency:  One time overflight of each area.
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  California Air Resources Board (Point of Contact: Jorn Herner); Debbie Gordon (Point of Contact: Rocky Mountain Institute)
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1727
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1727
Archived Data Citation:  Thorpe, A.K., B.D. Bue, D.R. Thompson, and R.M. Duren. 2019. Methane Plumes Derived from AVIRIS-NG over Point Sources across California, 2016-2017. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1727

Bounding Coordinates:
West Longitude:-125.77000 East Longitude:-113.73000
North Latitude:42.51000 South Latitude:32.35000

Product Title:  Sources of Methane Emissions (Vista-CA), State of California, USA
Start Date:  01/2005      End Date:  08/2019
Description:  This dataset provides spatial data products with identified and organized locations of potential methane (CH4) emitting facilities and infrastructure spanning the State of California. These data products form a GIS-based mapping database designed to address shortcomings in current CH4 source inventories and is known as Vista California (Vista-CA). Vista-CA consists of detailed spatial maps for facilities and infrastructure in California that are known or expected sources of CH4 emissions and illustrates the spatial distribution of potential CH4 sources. Vista-CA spatial data sets were created utilizing an assortment of publicly available data sources from local, state, and federal agencies for the years 2005 to 2019. The final Vista-CA database contains over 230,000 entries, which are presented as fifteen CH4 emitting infrastructure maps. The database was used to support flight planning and source attribution for the California Methane Survey project.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux; MRV
Keywords:  
Spatial Extent:  State of California, USA
Spatial Resolution:  points and polygons
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  CARB, CEC, BA-AQMD, SC-AQMD, Southern California Gas, PG&E, Sunshine Canyon Landfill Local Enforcement Agency, Republic Services (landfill operator)
Stakeholders:  California Air Resources Board (Point of Contact: Jorn Herner)
Current Application Readiness Level:  8
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1726
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1726
Archived Data Citation:  Hopkins, F.M., T. Rafiq, and R.M. Duren. 2019. Sources of Methane Emissions (Vista-CA), State of California, USA. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1726

Bounding Coordinates:
West Longitude:-124.36000 East Longitude:-114.49000
North Latitude:41.93000 South Latitude:32.54000

 
Publications: Carranza, V., Rafiq, T., Frausto-Vicencio, I., Hopkins, F. M., Verhulst, K. R., Rao, P., Duren, R. M., Miller, C. E. 2018. Vista-LA: Mapping methane-emitting infrastructure in the Los Angeles megacity. Earth System Science Data. 10(1), 653-676. DOI: 10.5194/essd-10-653-2018

Cusworth, D. H., Duren, R. M., Thorpe, A. K., Tseng, E., Thompson, D., Guha, A., Newman, S., Foster, K. T., Miller, C. E. 2020. Using remote sensing to detect, validate, and quantify methane emissions from California solid waste operations. Environmental Research Letters. 15(5), 054012. DOI: 10.1088/1748-9326/ab7b99

Cusworth, D. H., Duren, R. M., Yadav, V., Thorpe, A. K., Verhulst, K., Sander, S., Hopkins, F., Rafiq, T., Miller, C. E. 2020. Synthesis of Methane Observations Across Scales: Strategies for Deploying a Multitiered Observing Network. Geophysical Research Letters. 47(7). DOI: 10.1029/2020GL087869

Cusworth, D. H., Thorpe, A. K., Ayasse, A. K., Stepp, D., Heckler, J., Asner, G. P., Miller, C. E., Yadav, V., Chapman, J. W., Eastwood, M. L., Green, R. O., Hmiel, B., Lyon, D. R., Duren, R. M. 2022. Strong methane point sources contribute a disproportionate fraction of total emissions across multiple basins in the United States. Proceedings of the National Academy of Sciences. 119(38). DOI: 10.1073/pnas.2202338119

Duren, R. M., Thorpe, A. K., Foster, K. T., Rafiq, T., Hopkins, F. M., Yadav, V., Bue, B. D., Thompson, D. R., Conley, S., Colombi, N. K., Frankenberg, C., McCubbin, I. B., Eastwood, M. L., Falk, M., Herner, J. D., Croes, B. E., Green, R. O., Miller, C. E. 2019. California's methane super-emitters. Nature. 575(7781), 180-184. DOI: 10.1038/s41586-019-1720-3

Thorpe, A. K., Duren, R. M., Conley, S., Prasad, K. R., Bue, B. D., Yadav, V., Foster, K. T., Rafiq, T., Hopkins, F. M., Smith, M. L., Fischer, M. L., Thompson, D. R., Frankenberg, C., McCubbin, I. B., Eastwood, M. L., Green, R. O., Miller, C. E. 2020. Methane emissions from underground gas storage in California. Environmental Research Letters. 15(4), 045005. DOI: 10.1088/1748-9326/ab751d

Thorpe, A. K., O'Handley, C., Emmitt, G. D., DeCola, P. L., Hopkins, F. M., Yadav, V., Guha, A., Newman, S., Herner, J. D., Falk, M., Duren, R. M. 2021. Improved methane emission estimates using AVIRIS-NG and an Airborne Doppler Wind Lidar. Remote Sensing of Environment. 266, 112681. DOI: 10.1016/j.rse.2021.112681

Yadav, V., Duren, R., Mueller, K., Verhulst, K. R., Nehrkorn, T., Kim, J., Weiss, R. F., Keeling, R., Sander, S., Fischer, M. L., Newman, S., Falk, M., Kuwayama, T., Hopkins, F., Rafiq, T., Whetstone, J., Miller, C. 2019. Spatio-temporally Resolved Methane Fluxes From the Los Angeles Megacity. Journal of Geophysical Research: Atmospheres. 124(9), 5131-5148. DOI: 10.1029/2018JD030062

Archived Data Citations: Carranza, V., T. Rafiq, I. Frausto-Vicencio, F. Hopkins, K.R. Verhulst, P. Rao, R.M. Duren, and C.E. Miller. 2018. Sources of Methane Emissions (Vista-LA), South Coast Air Basin, California, USA. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1525

Hopkins, F.M., T. Rafiq, and R.M. Duren. 2019. Sources of Methane Emissions (Vista-CA), State of California, USA. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1726

Thorpe, A.K., B.D. Bue, D.R. Thompson, and R.M. Duren. 2019. Methane Plumes Derived from AVIRIS-NG over Point Sources across California, 2016-2017. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1727


 

Elvidge (CMS 2015) (2016)
Project Title:Global monitoring, reporting, and verification (MRV) system for carbon emissions from natural gas flaring

Science Team
Members:

Christopher (Chris) Elvidge, Colorado School of Mines (Project Lead)
Mikhail Zhizhin, University of Colorado

Solicitation:NASA: Carbon Monitoring System (2015)
Abstract: NOAA has developed a prototype MRV (monitoring, reporting and verification) system for global gas flaring. The purpose of this project is to reduce the uncertainties in the carbon emission estimates and produce a consistent time series of annual CO2 emission estimates for individual flare sites spanning 2012 through 2018. The monitoring system is based near-infrared and short-wave infrared nighttime data collected by the Visible Infrared Imaging Radiometer Suite (VIIRS). Peak radiant emissions from gas flares occur near 1.62 um - center of the VIIRS M11 spectral band. Using detections in multiple spectral bands, the algorithm calculates temperature, source size and radiant heat. Flares are separated from biomass burning and industrial sites based on temperature and persistence. More than 7000 flares were found each year in 2012-2014. Fire each flaring site, annual average radiant heat is calculated from the cloud-free observation set. The current calibration is based on national level flaring data reported by Cedigaz. The uncertainty in the current estimates exceeds the year-to-year differences in flared gas volumes from individual countries, calling into question the estimates. It is believed that the large uncertainties arise from country level errors in the Cedigaz estimates. Methods: Nighttime VIIRS data will be collected on a series of test flares burning a precisely controlled natural gas flow rates. Measurements will be made over a range of view angles and three flow rates (low, medium and high). Additional test flare events will explore the effects of multiple flares inside a VIIRS pixel and the effects of black carbon. From this test set, a new calibration will be developed for estimating flared gas volumes. The calibration will then be applied to VIIRS data spanning 2012-2018 resulting in both site specific and national estimates of CO2 emissions from natural gas flaring. Significance: The project meets on of the primary calls in the announcement – for proposals to develop MRV systems using remotely sensed data. There are three primary applications for the gas flaring MRV:  A. Emission reductions to meet Intended Nationally Determined Contributions (INDC): Countries need to have historical records and annual updates of their CO2 emissions from gas flaring. The data will be used to gauge the level of effort to be placed on gas flaring reduction. For countries with large flaring emissions, reductions in flaring may be enough to meet their INDC. Other countries with small flaring volumes may decide to focus their efforts on achieving their INDC targets in other sectors. Accurate gas flaring emission data are key to these decisions. The MRV data will also be used to document the INDC emission reductions from gas flaring. B. Zero Routine Flaring by 2013: The gas flaring MRV data are crucial this initiative. The MRV data will be used to identify the routine flares. This will likely be done based on duty cycle. Certainly flares detected 50-100% of the time are routine. As the duty cycle declines, at some point the flare will be deemed to be œnon-routine. The VIIRS data can be used to distinguish routine versus non- routine flaring once a decision has been made on the duty cycle threshold. For the routine flares, these can be tracked over time to document changes indicating the flare has been extinguished or converted to non-routine status. C. Low Carbon Fuel Standards (LCFS): Site specific MRV data can be assigned to specific production fields as one of the data sources used to calculate the carbon intensity of fuels. This approach can be used to establish flaring baseline for specific production fields and tracking of changes in flaring that count towards carbon emission reductions.
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Land-Atmosphere Flux
  • Global Surface-Atmosphere Flux
  • MRV

Participants:

Kimberly Baugh, University of Colorado
Christopher (Chris) Elvidge, Colorado School of Mines
Stephane Germain, GHGSat
Tilottama Ghosh, NOAA
Deborah (Debbie) Gordon, Rocky Mountain Institute (RMI)
Karen Griffin, U.S. Energy Information Administration
Bjorn Hamso, The World Bank
Martyn Howells, World Bank Global Gas Flaring Reduction Initiative (GGFR)
Feng Hsu, NOAA
Pietro Mezzano, Oil and Gas Climate Initiative
Frances (Fran) Reuland, Rocky Mountain Institute (RMI)
Stephanie Saunier, Carbon Limits
Hongjie Xie, University of Texas at San Antonio
Mikhail Zhizhin, University of Colorado

Project URL(s): None provided.
 
Data
Products:
Product Title:  
Description:  
Status:  
CMS Science Theme(s):  
Keywords:  
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

Product Title:  Global Gas Flare Survey by Infrared Imaging, VIIRS Nightfire, 2012-2019
Start Date:  01/2012      End Date:  12/2019     (2012-2019)
Description:  This dataset contains annual global flare site surveys from 2012-2019 derived from Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar Partnership (SNPP) satellite. Gas flaring sites were identified from heat anomalies first estimated by the VIIRS Nightfire (VNF) algorithm from which high-temperature biomass burning and low-temperature gas flaring were separated based on temperature and persistence. Nightly observations for each flare site were drawn to determine their activity in the given calendar year. Data include flare location, temperature, and estimated flared gas volume; flaring data summarized by country; and KMZ files for viewing flaring locations in Google Earth. This dataset is valuable for measuring the current status of global gas flaring, which can have significant environmental impacts.
Status:  Archived
CMS Science Theme(s):  MRV
Keywords:  Source, uncertainties & standard errors, evaluation. Methane gas flaring. VIIRS. Nationally Determined Contributions
Spatial Extent:  Global
Spatial Resolution:  point locations
Temporal Frequency:  annual
Input Data Products:  VIIRS Nightfire nightly infrared combustion source detections
Algorithm/Models Used:  Remote sensing for nighttime multispectral detection of IR combustion sources. Linear regression between the average radiant heat and flared gas volume.
Evaluation:  Calibrated with CEDIGAZ country-level annual gas flaring volume reports
Intercomparison Efforts/Gaps:  Ground-truth calibration with a single variable size flare is planned in 2017
Uncertainty Estimates:  10%
Uncertainty Categories:  Model-data comparison
Application Areas:  VIIRS Nightfire data provide site-specific tracking of natural gas flaring for use in evaluating efforts to reduce and eliminate routine flaring.
Relevant Policies/Programs:  Gas flaring regulations and reduction
Potential Users:  World Bank, state regulators, carbon cycle researchers
Stakeholders:  Carbon Limits (Point of Contact: Stéphanie Saunier stephanie.saunier@carbonlimits.no); Department of Geological Sciences, University of Texas at San Antonio (Point of Contact: Prof. Hongjie Xie hongjie.xie@utsa.edu); GHGsat (Point of Contact: Stephane Germain stephane.germain@ghgsat.com); Oil and Gas Climate Initiative (Point of Contact: Pietro Mezzano PietroM@ogci.com); Radia LLC (Point of Contact: Porter Montgomery porter@radia.com); U.S. DOE Energy Information Administration (EIA) (Point of Contact: Karen Griffin Karen.Griffin@eia.gov); World Bank Global Gas Flaring Reduction Initiative (GGFR) (Point of Contact: Martyn Howells hhowells@worldbank.org)
Current Application Readiness Level:  5
Start Application Readiness Level:  3
Target Application Readiness Level:  9
Future Developments:  Ground-truth calibration using a single flare with varying size and atmospheric conditions
Limitations:  Flares are observed 1-2 times per night. Can be masked by thick clouds. Diffrerences in flare design contribute to uncertainty.
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://eogdata.mines.edu/download_global_flare.html
Data Server URL(s):

https://eogdata.mines.edu/download_global_flare.html
Archived Data Citation:  Elvidge, C.D., and M. Zhizhin. 2021. Global Gas Flare Survey by Infrared Imaging, VIIRS Nightfire, 2012-2019. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1874

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

 
Publications: Elvidge, C. D., Bazilian, M. D., Zhizhin, M., Ghosh, T., Baugh, K., Hsu, F. 2018. The potential role of natural gas flaring in meeting greenhouse gas mitigation targets. Energy Strategy Reviews. 20, 156-162. DOI: 10.1016/j.esr.2017.12.012

Elvidge, C., Zhizhin, M., Baugh, K., Hsu, F., Ghosh, T. 2015. Methods for Global Survey of Natural Gas Flaring from Visible Infrared Imaging Radiometer Suite Data. Energies. 9(1), 14. DOI: 10.3390/en9010014

Elvidge, C., Zhizhin, M., Baugh, K., Hsu, F., Ghosh, T. 2019. Extending Nighttime Combustion Source Detection Limits with Short Wavelength VIIRS Data. Remote Sensing. 11(4), 395. DOI: 10.3390/rs11040395

Archived Data Citations: Elvidge, C.D., and M. Zhizhin. 2021. Global Gas Flare Survey by Infrared Imaging, VIIRS Nightfire, 2012-2019. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1874


 

Escobar (CMS 2015) (2016)
Project Title:CMS Applications: Stakeholder Engagement and Analysis of CMS Data Products in Decision Making and Policy Frameworks

Science Team
Members:

Vanessa Escobar, NASA GSFC / SSAI (Project Lead)
Jeffrey (Jeff) Masek, NASA GSFC (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2015)
Precursor Projects: Escobar (CMS 2013)  
Successor Projects: Poulter (CMS 2018)  
Abstract: Our team seeks to build upon and expand the current Carbon Monitoring System (CMS) Applications project (Escobar-2013) that assesses, identifies, and appropriately links existing decision support processes and policies to CMS carbon science. This CMS Applications effort aims to serve as a vehicle for facilitating and translating critical NASA science into decision support systems, establishing the science maturity and application readiness for NASA Headquarters and clearly stating the impact of CMS science to society for Congress. The partnerships fostered though this effort will lead to better utilization of NASA CMS data products, in turn leading to positive financial and societal outcomes. Our proposed work is highly relevant to the following activities listed as priorities for this call: 1) understanding and engaging the user community for carbon monitoring products; 2) evaluating current and planned NASA CMS products with regard to their value for decision making by identified users and to assist in having existing products used for stakeholder activities; 3) conducting MRV-related work in support of international REDD or REDD+ projects, as well as studies of stakeholder interests; 4) assessing the NASA CMS applications program though a 'lessons learned' document which evaluates the number of potential and actual CMS data users.  During the next phase of funding our team will focus efforts on several fronts. First, we will continue to develop the translation tools created during the Escobar-2013 project, and relate CMS product capabilities to stakeholder needs through the use tutorials, short science articles, white papers, and policy briefs. that identify thematic opportunities, identify data gaps and sync the CMS science research to the beneficiary of the data (stakeholder). Workshops events and the CMS Policy Speaker Series will continue to serve as tools for highlighting carbon relevant policies and identifying the science needs of operational organizations. Furthermore, we will develop a systematic evaluation of these workshops and policy series with follow-up surveys and reports in an effort to assess the societal relevance of our activities. Our team will conduct science policy bridging with organizations such as (but not limited to) RGGI, EPA, USGS, 3DEP, USGCRP, Chesapeake Bay Restoration Program, USDA Environmental Markets and the Department of Natural Resources for Maryland, Delaware, Pennsylvania and Sonoma County, CA and USGCRP. These partners were identified in the Escobar 2013 Applications work and a clear understanding of their needs and objectives will be expanded on for the 2016 efforts. We will also collaborate closely with the Carbon Cycle Interagency Working Group of the U.S Global Change Research Program, and contribute to carbon-related reports, such as the SOCCR-2 and the Fourth National Climate Assessment. Of equal importance is merging the diversity of the CMS Initiative with ongoing and future NASA missions and programs. These cross-mission collaborations are essential for broadening the reach and relevance of CMS science. The proposed CMS Applications effort will leverage opportunities with newer missions like SMAP and OCO-2 while also planning for future synergy with ICESat-2, NISAR and ASCENDS. Finally, research to assess the impact and value of the CMS data in specific case studies will be conducted in collaboration with the Joint Global Change Research Institute (JGCRI), collaboration between the U.S DoE Pacific Northwest National Laboratory (PNNL) and the University of Maryland at College Park.
Project Associations:
  • CMS
CMS Primary Theme:
  • MRV
CMS Science Theme(s):
  • Decision Support
  • MRV

Participants:

Phillip Abbott, Purdue University
Molly Brown, University of Maryland
Kalyn Dorheim, Pacific NW National Lab
Christine Dragisic, U.S. Department of State
Jae Edmonds, Pacific Northwest National Laboratory's Joint Global Change Research Institute
Vanessa Escobar, NASA GSFC / SSAI
Dwight Gledhill, NOAA Ocean Acidification Program
Deborah (Debbie) Gordon, Rocky Mountain Institute (RMI)
Peter Griffith, NASA GSFC
Corinne Hartin, U.S. EPA
Chris Hartley, USDA Environmental Markets Division
George Hurtt, University of Maryland
Fred Lipschultz, U.S. Global Change Research Program
Jeffrey (Jeff) Masek, NASA GSFC
Eleanor Milne, Global Environmental Facility's (GEF) Carbon Benefits Project, Colorado State University
Joanna Post, UNFCCC
David Reidmiller, USGS
Frances (Fran) Reuland, Rocky Mountain Institute (RMI)
James Whetstone, National Institute of Standards and Technology (NIST)

Project URL(s): None provided.
 
Data
Products:
Product Title:  CMS Applications Case Studies
Time Period:  2017 - 2019
Description:  To document the value of CMS information products, we will perform a set of quantitative case studies to highlight the social and economic benefits of CMS, focusing on the EPA and USFS. The case studies provide a qualitative assessment of the societal relevance of that science data on a decision process or policy.
Status:  Planned
CMS Science Theme(s):  Decision Support
Keywords:  Evaluation & User Interface
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  For this case study we will use an integrated assessment model to study the socio-economic value of select CMS products in stakeholder organizations (EPA and USFS).
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - MRV; - GHG emissions inventory
Relevant Policies/Programs:  Any EPA or USFS policy or program that may benefit from incorporating carbon information into decision-making.
Potential Users:  USDA Forest Service and EPA, as well as other CMS data product end users
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

Product Title:  CMS Applications Policy Speaker Series
Time Period:  2017 - 2019
Description:  Inform the CMS product developers of the information scale and decision domain of stakeholders, policy makers, and potential end-users.
Status:  Preliminary
CMS Science Theme(s):  Decision Support
Keywords:  Evaluation & User Interface
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - MRV; - GHG emissions inventory; - Land management; - Forest inventory; - Fire management; - Invasive species; - Watershed protection plans; - Ocean acidification mitigation; - Fisheries regulations; - Coastal land management; - Air quality protection
Relevant Policies/Programs:  Any policy or program that may benefit from incorporating carbon information in decision-making. (i.e. NGHGI, FIA, Maryland Forest Preservation Act of 2013, CA-AB32, Chesapeake Bay Program, Sonoma County Vegetation Mapping and LiDAR Program, Indonesia's National Action Plan for Reducing Greenhouse Gas Emissions, FOARAM, Blue Carbon Initiative, RGGI, FLPMA, REDD+, Carbon Fund of Forest Carbon Partnership Facility, CAA, CAP, NACP, IPCC, U.S. Farm Bill)
Potential Users:  Any carbon scientist or stakeholder who is interested in transitioning carbon science products to decision-making frameworks.
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  Summaries of all the seminars will be made available on the Policy Speaker Series webpage.
Limitations:  Suggestions for speakers and topics of interest from the CMS community are encouraged.
Date When Product Available:  On-going monthly seminars
Metadata URL(s):
Data Server URL(s):

http://carbon.nasa.gov/policy_series.html
Archived Data Citation:  

Product Title:  CMS Data Product Tutorials
Description:  Meetings are set up to discuss CMS products derived from multiple projects missions. Tutorials provide the opportunity to leverage innovation for how to best combine data sets from different CMS projects to meet the needs of stakeholders and decision makers. Tutorials are hosted by an end user institution like USDA or USGS but are organized and managed by the CMS Applications team.
Status:  Planned
CMS Science Theme(s):  Decision Support
Keywords:  Evaluation & User Interface
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  MRV; - GHG emissions inventory; - Land management; - Forest inventory; - Fire management; - Invasive species; - Watershed protection plans; - Ocean acidification mitigation; - Fisheries regulations; - Coastal land management; - Air quality protection
Relevant Policies/Programs:  Any policy or program that may benefit from incorporating carbon information in decision-making. (i.e. NGHGI, FIA, Maryland Forest Preservation Act of 2013, CA-AB32, Chesapeake Bay Program, Sonoma County Vegetation Mapping and LiDAR Program, Indonesia's National Action Plan for Reducing Greenhouse Gas Emissions, FOARAM, Blue Carbon Initiative, RGGI, FLPMA, REDD+, Carbon Fund of Forest Carbon Partnership Facility, CAA, CAP, NACP, IPCC, U.S. Farm Bill)
Potential Users:  Any stakeholder who is interested in transitioning carbon science products to decision-making frameworks. (i.e. NASA, CCIWG, DOE, EPA, USDA, USFS, NOAA, USGS, USAID, State Department, California Air Resources Board, Sonoma County Agricultural Preservation and Open Space District, Conservation International, Ocean Conservancy, Maryland DNR, Maryland Forest Service, Delaware DNREC, Pennsylvania DCNR Bureau of Forestry)
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

Product Title:  CMS Products Fact Sheet and Application Readiness Level (ARL) figures for all 2012-2016 projects
Time Period:  2012-2016
Description:  Provide tools and activities that translate the CMS science in a way that will allow stakeholders and decision makers understand the capabilities of the CMS science products.
Status:  Preliminary
CMS Science Theme(s):  Decision Support
Keywords:  Evaluation & User Interface
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - MRV; - GHG emissions inventory; - Land management; - Forest inventory; - Fire management; - Invasive species; - Watershed protection plans; - Ocean acidification mitigation; - Fisheries regulations; - Coastal land management; - Air quality protection;
Relevant Policies/Programs:  Any policy or program that may benefit from incorporating carbon information in decision-making. (i.e. NGHGI, FIA, Maryland Forest Preservation Act of 2013, CA-AB32, Chesapeake Bay Program, Sonoma County Vegetation Mapping and LiDAR Program, Indonesia's National Action Plan for Reducing Greenhouse Gas Emissions, FOARAM, Blue Carbon Initiative, RGGI, FLPMA, REDD+, Carbon Fund of Forest Carbon Partnership Facility, CAA, CAP, NACP, IPCC, U.S. Farm Bill)
Potential Users:  In addition to CMS science team, any stakeholder who is interested in transitioning carbon science products to decision-making frameworks. (i.e. NASA, CCIWG, DOE, EPA, USDA, USFS, NOAA, USGS, USAID, State Department, California Air Resources Board, Sonoma County Agricultural Preservation and Open Space District, Conservation International, Ocean Conservancy, Maryland DNR, Maryland Forest Service, Delaware DNREC, Pennsylvania DCNR Bureau of Forestry)
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  ARL Tables will be archived at the ORNL DAAC as 'non-traditional' products.
Limitations:  CMS products search capability is not yet user-friendly. The spreadsheet is very large and difficult to reduce to 1-3 pages. Currently format is limited to Excel or PDF formats.
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):

http://carbon.nasa.gov/CMS_products_fact_sheet.html

http://carbon.nasa.gov/app_readiness.html
Archived Data Citation:  

Product Title:  Evaluation of stakeholders' end uses of CMS products
Description:  Broaden and strengthen the knowledge of CMS data products by engaging the research and applications communities that will benefit from the CMS initiative. Explore ways to evaluate the impact of CMS data products on decision making.
Status:  Planned
CMS Science Theme(s):  Decision Support
Keywords:  Evaluation & User Interface
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - MRV; - GHG emissions inventory; - Land management; - Forest inventory; - Fire management; - Invasive species; - Watershed protection plans; - Ocean acidification mitigation; - Fisheries regulations; - Coastal land management; - Air quality protection
Relevant Policies/Programs:  Any policy or program that may benefit from incorporating carbon information into decision-making. (i.e. NGHGI, FIA, Maryland Forest Preservation Act of 2013, CA-AB32, Chesapeake Bay Program, Sonoma County Vegetation Mapping and LiDAR Program, Indonesia's National Action Plan for Reducing Greenhouse Gas Emissions, FOARAM, Blue Carbon Initiative, RGGI, FLPMA, REDD+, Carbon Fund of Forest Carbon Partnership Facility, CAA, CAP, NACP, IPCC, U.S. Farm Bill)
Potential Users:  Any stakeholder who is interested in transitioning carbon science products to decision-making frameworks. (i.e. NASA, CCIWG, DOE, EPA, USDA, USFS, NOAA, USGS, USAID, State Department, California Air Resources Board, Sonoma County Agricultural Preservation and Open Space District, Conservation International, Ocean Conservancy, Maryland DNR, Maryland Forest Service, Delaware DNREC, Pennsylvania DCNR Bureau of Forestry)
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  Continue working with the Maryland Department of Natural Resources and other state agencies in the ti-state area of Maryland, Delaware, and Pennsylvania for incorporation of CMS products in state and county scaled decision-making.
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):

http://carbon.nasa.gov/applications.html
Archived Data Citation:  

Product Title:  Applications Workshops and Reports
Time Period:  2017 - 2019
Description:  Applications workshops are integrated with the CMS Science team meetings and coordinated with the Science Team lead and Carbon Cycle and Ecosystems (CC&E) Office in order to match CMS science and stakeholder needs. The workshops will provide feedback to the NASA CMS scientists and NASA Headquarters about CMS product applications (successes, policy targets, concerns, challenges and proposed solutions) and will be held annually during the CMS Science Team Meetings. We expect the stakeholders to provide feedback to the CMS community on the following elements:
1. Description of Work 

2. CMS Data Product(s) being used
3. Policies and Decision Making Timelines

4. Additional carbon data needs
5. Evaluation of value of CMS product for organization’s goal
Status:  Planned
CMS Science Theme(s):  Decision Support
Keywords:  Evaluation & User Interface
Spatial Extent:  Variable
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - MRV; - GHG emissions inventory; - Land management; - Forest inventory; - Fire management; - Invasive species; - Watershed protection plans; - Ocean acidification mitigation; - Fisheries regulations; - Coastal land management; - Air quality protection
Relevant Policies/Programs:  Any policy or program that may benefit from incorporating carbon information in decision-making. (i.e. NGHGI, FIA, Maryland Forest Preservation Act of 2013, CA-AB32, Chesapeake Bay Program, Sonoma County Vegetation Mapping and LiDAR Program, Indonesia's National Action Plan for Reducing Greenhouse Gas Emissions, FOARAM, Blue Carbon Initiative, RGGI, FLPMA, REDD+, Carbon Fund of Forest Carbon Partnership Facility, CAA, CAP, NACP, IPCC, U.S. Farm Bill)
Potential Users:  Any stakeholder who is interested in transitioning carbon science products to decision-making frameworks. (i.e. NASA, CCIWG, DOE, EPA, USDA, USFS, NOAA, USGS, USAID, State Department, California Air Resources Board, Sonoma County Agricultural Preservation and Open Space District, Conservation International, Ocean Conservancy, Maryland DNR, Maryland Forest Service, Delaware DNREC, Pennsylvania DCNR Bureau of Forestry)
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  - Develop a lessons learned document which includes feedback from CMS stakeholder and end users on their carbon data needs, and impact of CMS data products on their organization's activities.
Limitations:  A workshop can sometimes only target one specific audience or topic at a time. The quality of workshop outcomes is dependent on feedback, participation and willing to provide transparent needs (science and stakeholders).
Date When Product Available:  On-going annual workshops
Metadata URL(s):
Data Server URL(s):

http://carbon.nasa.gov/app_workshops.html
Archived Data Citation:  

 
Publications: Brown, M. E., Cooper, M. W., Griffith, P. C. 2020. NASA's carbon monitoring system (CMS) and arctic-boreal vulnerability experiment (ABoVE) social network and community of practice. Environmental Research Letters. 15(11), 115014. DOI: 10.1088/1748-9326/aba300

Brown, M. E., Ihli, M., Hendrick, O., Delgado-Arias, S., Escobar, V. M., Griffith, P. 2016. Social network and content analysis of the North American Carbon Program as a scientific community of practice. Social Networks. 44, 226-237. DOI: 10.1016/j.socnet.2015.10.002

Kaushik, A., Graham, J., Dorheim, K., Kramer, R., Wang, J., Byrne, B. 2020. The Future of the Carbon Cycle in a Changing Climate. Eos. 101. DOI: 10.1029/2020EO140276


 

Fatoyinbo (CMS 2015) (2016)
Project Title:Future Mission Fusion for High Biomass Forest Carbon Accounting

Science Team
Members:

Temilola (Lola) Fatoyinbo, NASA GSFC (Project Lead)
Laura Duncanson, University of Maryland
Amy Neuenschwander, University of Texas

Solicitation:NASA: Carbon Monitoring System (2015)
Abstract: Objectives The primary objectives of our research are: (1) To independently quantify the relationship between biomass density and expected error from GEDI, NISAR and ICESat-2 in high AGB forests in Sonoma County, Costa Rica, and Gabon; (2) To identify the sources of error in high biomass forests for each mission, including from field estimates (GPS error, allometry), from errors in the airborne/spaceborne data (penetration to the ground), and from errors in empirical modeling; (3) To assess data fusion techniques in order to increase the accuracy of AGB estimation through the integration of the airborne simulators for the three missions; (4) To provide AGB stock and error maps to local stakeholders through a user-friendly web portal, enabling the estimation of total AGB and expected error specifically within areas of local interest. Methods/Techniques The proposed research focuses on establishing the relationship between AGB density and estimation error for each of three future active remote sensing NASA missions using three study areas with high AGB forests. We propose to use existing airborne datasets that have been collected over forests in Gabon, Costa Rica, and Sonoma County, and to process these datasets to simulate NISAR, ICESAT-2, and GEDI.  Field data have already been collected in all three study sites. New field data will also be collected in particularly high biomass areas of Sonoma County. Finally, Terrestrial Laser Scanning (TLS) data will be collected in Sonoma County, as well as provided to the research team from existing collections in Gabon. This TLS data will quantify existing or expected errors in field estimates of AGB. LVIS and discrete return Airborne Laser Scanning (ALS) data are the data sources used to simulate GEDI, through a GEDI waveform simulator already under development at the University of Maryland. LVIS data has already been collected in Costa Rica and Gabon, and ALS has been collected in Sonoma County. ALS data will also be used to simulate ICESAT-2’s ATLAS dataset, through a photon counting simulation already tested using ALS data in Gabon. This simulation will be expanded to Sonoma County. Finally, UAVSAR will be used to simulate NISAR. Metrics gleaned from each simulation product will be used to build mission-independent AGB stock and error models for each of the three datasets. Finally, a prototype design for future mission fusion will be developed to capitalize on the three independent sets of structural observations from GEDI, ICESAT-2 and NISAR. All AGB and error maps will be provided to local stakeholders via a cloud-based GIS software package, Ecometrica, which will enable the manipulation of maps to perform carbon accounting for locally relevant land management activities. Perceived Significance Through comparing future mission utility on a shared set of field observations, the proposed research will provide a precise and comparable quantification of expected errors from GEDI, ICESAT-2, and NISAR in high AGB forests. Additionally, methods will be tested to fuse these three future datasets with the intention of developing best practices for AGB and error MRV. By working with scientists from each of the three missions’science teams, this research will provide an unbiased analysis of the strengths and weaknesses of the future missions and inform the development of the next generation of NASA active RS instruments. Additionally, by working with local stakeholders both in the US and abroad, the proposed research will facilitate knowledge and data transfer from data developers to data users in the hopes that best practices can be developed to optimize the utility of future missions products for carbon monitoring initiatives, such as REDD+.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • MRV

Participants:

Mathias Disney, University College London
Ralph Dubayah, University of Maryland
Laura Duncanson, University of Maryland
Temilola (Lola) Fatoyinbo, NASA GSFC
Michelle Hofton, University of Maryland
Ghislain Moussavou, Agence Gabonaise d'Etudes et d'Observations Spatiales
Amy Neuenschwander, University of Texas
Aurelie Shapiro, World Wildlife Fund
Marc (Mac) Simard, Jet Propulsion Laboratory / Caltech
Nathan Thomas, NASA GSFC / ESSIC UMD
Carl Trettin, U.S. Forest Service Southern Research Station
Jan-Willem van Bochove, United Nations Environment Programme World Conservation Monitoring Centre
Mauricio Vega-Araya, CIECO

Project URL(s): None provided.
 
Data
Products:
Product Title:  AGB stock and error maps with associated uncertainties for Costa Rica
Time Period:  Corresponding to data acquisitions. Sonoma: 2014, Costa Rica: 2009, Gabon: 2016
Description:  Fused AGB stock and error maps from simulated fused GEDI, NISAR & ICESAT-2 over La Selva Biological Research Station, Costa Rica
Status:  Preliminary
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  Costa Rica
Spatial Resolution:  0.25 ha – 1 ha
Temporal Frequency:  Stock maps (one time only)
Input Data Products:  Airborne lidar (Sonoma: ALS, Costa Rica: LVIS, Gabon, LVIS), and UAVSAR
Algorithm/Models Used:  GEDI, ICESAT2 and NISAR simulated from airborne proxies, and biomass is empirically derived algorithms developed in this research
Evaluation:  Cross validation against field plot estimates of biomass
Intercomparison Efforts/Gaps:  NA
Uncertainty Estimates:  Error propagated through field data to plot level, through empirical models and mapped to produce 95th percentile confidence interval around pixel estimates.
Uncertainty Categories:  Model-Data comparisons
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  Local stakeholders as identified in proposal
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  4
Target Application Readiness Level:  7
Future Developments:  Web portal(s) to be propagated with biomass maps & uncertainties for stakeholders (Ecometrica in Sonoma, WRI-based web portal in Gabon)
Limitations:  These are simulation-based results and represent only predicted mission data performance for biomass. Actual mission datasets may differ based on on-orbit performance, cloud cover, etc.
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  CMS: LiDAR Biomass Improved for High Biomass Forests, Sonoma County, CA, USA, 2013
Start Date:  09/2013      End Date:  09/2013     (2013)
Description:  This data set provides estimates of above-ground woody biomass and uncertainty at 30-m spatial resolution for Sonoma County, California, USA, for the nominal year 2013. Biomass estimates, megagrams of biomass per hectare (Mg/ha), were generated using a combination of airborne LiDAR data and field plot measurements with a parametric modeling approach. The relationship between field estimated and airborne LiDAR estimated aboveground biomass density is represented as a parametric model that predicts biomass as a function of canopy cover and 50th percentile and 90th percentile LiDAR heights at a 30-m resolution. To estimate uncertainty, the biomass model was re-fit 1,000 times through a sampling of the variance-covariance matrix of the fitted parametric model. This produced 1,000 estimates of biomass per pixel. The 5th and 95th percentiles, and the standard deviation of these pixel biomass estimates, were calculated.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  Sonoma County, California, USA
Spatial Resolution:  The data set has no explicit temporal component. Data are nominally for the year 2013
Temporal Frequency:  Grid cells at 30-meter resolution
Input Data Products:  LiDAR data were acquired over Sonoma County by Watershed Sciences Inc (WSI) in September – November of 2013 covering ~440,000 ha (44 flights). Airborne discrete return LiDAR instrument - Leica ALS70 sensor was mounted on a Cessna Grand Caravan at 14 points m-2 (Dubayah et al., 2013). Field plot data included the 166 field plots from Dubayah et al. (2017) and 30 new field reference plots that were randomly sampled in tall (>30 m) forests across the County. Field plots were measured as variable radius plots that were distributed as a stratified random sample across the county. The additional 30 plots were sampled randomly from tall forests (>30m) from a layer of land accessibility.
Algorithm/Models Used:  The relationship between field estimated and airborne LiDAR estimated aboveground biomass density used a parametric model that predicts biomass as a function of %Canopy Cover (Dubayah et al., 2017), and 50th percentile and 90th percentile LiDAR heights at a 30-m resolution.
Evaluation:  
Intercomparison Efforts/Gaps:  This revised product was compared to the original product both in terms of the model fit, in areas of known high biomass (e.g. redwood groves), and per pixel across the full County.
Uncertainty Estimates:  To estimate per-pixel uncertainty, the biomass model was re-fit 1,000 times through a sampling of the variance-covariance matrix of the fitted parametric model. This produced 1,000 estimates of biomass per pixel. The 5th and 95th percentile, as well as the standard deviation of these pixel estimates, were calculated. Note that error was not propagated from field estimations
Uncertainty Categories:  
Application Areas:  Forest conservation, land management, GHG accounting, Forest Management
Relevant Policies/Programs:  California Environmental Protection Agency Air Resources Board Compliance Offset U.S. Forest Projects
Potential Users:  Sonoma County Agricultural Preservation and Open Space District, California State Parks, Redwood National and State Parks
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  5
Target Application Readiness Level:  6
Future Developments:  
Limitations:  This product is primarily focused on improving high biomass forest carbon estimated for 1) those interested in forest carbon accounting and forest conservation in Sonoma County and 2) those interested in comparing satellite biomass products to higher quality reference datasets. Note that the uncertainties reported in the product do not include uncertainties from allometric models (i.e. from field estimates), and thus are underestimates of true uncertainties.
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1764
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1764
Archived Data Citation:  Duncanson, L., R.O. Dubayah, J. Armston, M. Liang, A. Arthur, and D. Minor. 2020. CMS: LiDAR Biomass Improved for High Biomass Forests, Sonoma County, CA, USA, 2013. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1764

Bounding Coordinates:
West Longitude:-123.54000 East Longitude:-122.34000
North Latitude:38.85000 South Latitude:38.11000

 
Publications: Disney, M., Burt, A., Wilkes, P., Armston, J., Duncanson, L. 2020. New 3D measurements of large redwood trees for biomass and structure. Scientific Reports. 10(1). DOI: 10.1038/s41598-020-73733-6

Duncanson, L., Armston, J., Disney, M., Avitabile, V., Barbier, N., Calders, K., Carter, S., Chave, J., Herold, M., Crowther, T. W., Falkowski, M., Kellner, J. R., Labriere, N., Lucas, R., MacBean, N., McRoberts, R. E., Meyer, V., Naesset, E., Nickeson, J. E., Paul, K. I., Phillips, O. L., Rejou-Mechain, M., Roman, M., Roxburgh, S., Saatchi, S., Schepaschenko, D., Scipal, K., Siqueira, P. R., Whitehurst, A., Williams, M. 2019. The Importance of Consistent Global Forest Aboveground Biomass Product Validation. Surveys in Geophysics. 40(4), 979-999. DOI: 10.1007/s10712-019-09538-8

Duncanson, L., Neuenschwander, A., Hancock, S., Thomas, N., Fatoyinbo, T., Simard, M., Silva, C. A., Armston, J., Luthcke, S. B., Hofton, M., Kellner, J. R., Dubayah, R. 2020. Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California. Remote Sensing of Environment. 242, 111779. DOI: 10.1016/j.rse.2020.111779

Silva, C. A., Duncanson, L., Hancock, S., Neuenschwander, A., Thomas, N., Hofton, M., Fatoyinbo, L., Simard, M., Marshak, C. Z., Armston, J., Lutchke, S., Dubayah, R. 2021. Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping. Remote Sensing of Environment. 253, 112234. DOI: 10.1016/j.rse.2020.112234

Archived Data Citations: Duncanson, L., R.O. Dubayah, J. Armston, M. Liang, A. Arthur, and D. Minor. 2020. CMS: LiDAR Biomass Improved for High Biomass Forests, Sonoma County, CA, USA, 2013. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1764


 

Izaurralde (CMS 2015) (2016)
Project Title:Cropland Carbon Monitoring System (CCMS): A satellite-based system to estimate carbon fluxes on U.S. Croplands

Science Team
Members:

Roberto (Cesar) Izaurralde, University of Maryland (Project Lead)
Varaprasad (Prasad) Bandaru, USDA ARS

Solicitation:NASA: Carbon Monitoring System (2015)
Successor Projects: Bandaru (CMS 2020)  
Abstract: Croplands are considered to have large CO2 offset capacity. However, it is highly uncertain how much CO2 stabilization can be achieved through land management strategies as croplands are expected to meet increasing demands for food and bioenergy production. The impacts of land use and land management practices on carbon (C) cycling should be anticipated when developing recommended strategies and policies; otherwise, they may induce unintended loss of CO2 to the atmosphere and render croplands as C sources. Lack of a cropland C monitoring system that captures the complexity of cropland C cycling and provides fine-scale and accurate C flux estimates hinders the development of effective joint policies and integrated sustainable carbon management strategies targeting CO2 offset potentials. Current methods for cropland C monitoring yield unreasonable regional flux estimates as they lack spatially resolved crop parameters and management practices. Satellite remote sensing is a strong tool for estimating spatially distributed vegetative characteristics (e.g. crop phenology and LAI) and crop parameters (e.g. land cover and land use change, crop species, crop rotations) used in agroecosystem models. As part of the Global Agricultural Monitoring (GEO-GLAM) program, which is jointly funded by NASA and USDA, we have developed a remote-sensing version of the mechanistic agroecosystem model EPIC, herein referred to as RS-EPIC, which utilizes satellite remote sensing data to improve crop characterization and simulation of crop productivity, soil C storage and C fluxes. The overall scientific goal of this proposal is to develop a Cropland C Monitoring System (CCMS) prototype that improves upon cropland C storage and flux estimates developed under previous NASA CMS activities in terms of spatial and temporal scale and completeness. As a first objective of this goal, we will integrate satellite-derived crop specific characterization of vegetation and management, off-shelf ancillary spatial databases and the RS-EPIC model to estimate seasonal and annual C cycle components including net primary production (NPP), net ecosystem productivity (NEP), harvested C, lateral soil C fluxes and net ecosystem C balance (NECB). These estimates will be produced for corn, soybean, wheat, sorghum, cotton, alfalfa, barley, rice and peas crops grown in the conterminous US at a spatial resolution of 500 m for 2015-2016. Together, the nine major crops grown cover approximately 96% of US cropland area. Three additional objectives are: 1) estimate uncertainty of C storage and fluxes estimated by the CCMS prototype; 2) engage with national agencies to evaluate the CCMS consistency with existing C inventories; 3) conduct a scoping study to evaluate remote sensing methods for mapping soil tillage at large scales. Ultimately, the CCMS products developed under this project will provide the knowledge base at relevant spatial and temporal scales for understanding complex C cycling outcomes under various land use and land management practices and developing joint policies to meet multiple objectives (e.g. food and energy security) while contributing to stabilize atmospheric CO2. Other potential uses of the CCMS include: 1) use in economic models to determine incentive levels for C management options; 2) integration into hydrological models to assess impacts on aquatic ecosystems; 3) incorporation into regional integrated assessment models to understand contributions of regional management practices to global climate change; 4) use of NPP estimates to interpret the top-bottom CO2 estimates 5) enhancement of EPA reporting of CO2 offset potentials on croplands.
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • Decision Support
  • MRV

Participants:

Varaprasad (Prasad) Bandaru, USDA ARS
Craig Daughtry, USDA
Prasanna Gowda, USDA
George Hurtt, University of Maryland
Roberto (Cesar) Izaurralde, University of Maryland
Curtis Jones, University of Maryland
Christopher (Chris) Justice, University of Maryland
Ramakrishna (Rama) Nemani, NASA ARC
Ritvik Sahajpal, University of Maryland
Fernando Sedano, University of Maryland
Mona Lisa Williams, University of Maryland

Project URL(s): None provided.
 
Data
Products:
Product Title:  Net Primary Production (NPP), Net Ecosystem Exchange (NEE), Lateral Carbon Loss (LCL) and Net Ecosystem Carbon Balance (NECB) 500m products for croplands in Nebraska for 2015 and 2016
Time Period:  2012 & 2015
Description:  The product includes estimates of net primary production for individual crops grown in Nebraska for years 2015 and 2016 at spatial resolution of 500m
Status:  Preliminary
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Crops, carbon monitoring, Net Primary Production (NPP), Net Ecosystem Exchange (NEE), Lateral Carbon Loss (LCL), Net Ecosystem Carbon Balance (NECB)
Spatial Extent:  Nebraska
Spatial Resolution:  500 m
Temporal Frequency:  8-day and annual
Input Data Products:  MODIS, LANDSAT, SSURGO soil, PRISM weather, USDA Cropland data layer
Algorithm/Models Used:  RS-EPIC model
Evaluation:  Validate with flux tower data
Intercomparison Efforts/Gaps:  Comparison with Airborn CO2 measurements and /or other modeling approaches
Uncertainty Estimates:  Uncertainty in the estimates will be quantify by comparing with flux tower measurements and USDA-NASS regional biomass estimates
Uncertainty Categories:  Deterministic
Application Areas:  Agricultural productivity; carbon management in agriculture; Carbon accounting and reporting; Soil and water quality
Relevant Policies/Programs:  USDA regional climate hub programs; USDA Conservation Effects Assessment Program; EPA national inventory program
Potential Users:  USDA regional climate hub programs; USDA Conservation Effects Assessment program; EPA inventory program
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  
Limitations:  Data format will be geotiff files so users that are not familiar with geotiff format may not be able to use the product.
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Net Primary Production (NPP), Net Ecosystem Exchange (NEE), Lateral Carbon Loss (LCL) and Net Ecosystem Carbon Balance (NECB) 500m products for major crops (Corn, Soybean, Winter wheat, Spring wheat, Cotton, Sorghum, Rice, Barley, Alfalfa, and Pea) croplands in Conterminous US for 2015 and 2016
Time Period:  2012 & 2015
Description:  The product includes estimates of net primary production for individual crops grown in U.S for years 2015 and 2016 at spatial resolution of 500m
Status:  Preliminary
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Crops, carbon monitoring, Net Primary Production (NPP), Net Ecosystem Exchange (NEE), Lateral Carbon Loss (LCL), Net Ecosystem Carbon Balance (NECB)
Spatial Extent:  CONUS
Spatial Resolution:  500 m
Temporal Frequency:  8-day and annual
Input Data Products:  MODIS, LANDSAT, SSURGO soil, PRISM weather, USDA Cropland data layer
Algorithm/Models Used:  RS-EPIC model
Evaluation:  Validate with flux tower data
Intercomparison Efforts/Gaps:  Comparison with Airborn CO2 measurements and /or other modeling approaches
Uncertainty Estimates:  Uncertainty in the estimates will be quantify by comparing with flux tower measurements and USDA-NASS regional biomass estimates
Uncertainty Categories:  Deterministic
Application Areas:  Agricultural productivity; carbon management in agriculture; Carbon accounting and reporting; Soil and water quality
Relevant Policies/Programs:  USDA regional climate hub programs; USDA Conservation Effects Assessment Program; EPA national inventory program
Potential Users:  USDA regional climate hub programs; USDA Conservation Effects Assessment program; EPA inventory program
Stakeholders:  
Current Application Readiness Level:  4
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  Stakeholder meeting will be held in May 2020 to demonstrate the utility of product in carbon management, carbon policy activities.
Limitations:  Data format will be geotiff files so users that are not familiar with geotiff format may not be able to use the product.
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

 
Publications: Bandaru, V., Yaramasu, R., PNVR, K., He, J., Fernando, S., Sahajpal, R., Wardlow, B. D., Suyker, A., Justice, C. 2020. PhenoCrop: An integrated satellite-based framework to estimate physiological growth stages of corn and soybeans. International Journal of Applied Earth Observation and Geoinformation. 92, 102188. DOI: 10.1016/j.jag.2020.102188


 

Kawa (CMS 2015) (2016)
Project Title:Airborne Eddy Flux Measurements for Validation/Evaluation of High-Resolution MRV Systems

Science Team
Members:

Stephan (Randy) Kawa, NASA GSFC (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2015)
Abstract: Progress in the Carbon Monitoring System (CMS) demands rigorous evaluation and quantitative uncertainty characterization in all products and analyses. A range of validation approaches is used, but comprehensive evaluation is challenging, often limited in coverage, representativeness, and precision. The guiding science question for this proposal is: how best to validate CMS regional-scale products and how well can this be done? We aim to expand the current scope of validation methods for CMS through acquisition and analysis of airborne eddy covariance carbon flux observations. Specifically, we will address the question: How can real-time flux measurements over regional length scales contribute to validation of the products and processes inherent in designing a high- resolution Monitoring, Reporting, and Verification (MRV) system? We will do this within the framework of a prototype system for monitoring carbon stocks and fluxes under development for CMS at the University of Maryland (UMD). Airborne eddy covariance is a powerful observational tool capable of providing near- direct measurements of surface-atmosphere exchange at ecosystem and policy relevant scales of 1 – 100 km. Our group at GSFC has assembled a system for measurement of CO2, CH4, H2O, and heat fluxes based on the NASA Sherpa aircraft. The Sherpa provides a versatile, economical platform for measuring greenhouse gas (GHG) fluxes to be used in evaluating top-down and bottom-up source/sink estimates for a wide range of applications, including evaluation of biophysical process models as well as validation of top-level satellite flux products from OCO-2 and other carbon space missions. The system is supported and scheduled for installation, flight-testing, and science demonstration over the Maryland Eastern Shore during July-Sept 2016. To address uncertainties in the high-resolution MRV system we will focus on measuring and evaluating the ecosystem model processes used to connect vegetation metabolism to biomass change and, hence, integrated carbon flux. The analysis will compare flux data and modeling across gradients of forest height and type as well as soil and climate regime within the US Mid-Atlantic region. We will also use the airborne flux data to assess uncertainties in scaling up from local to regional and larger domains. This will include leveraging of the flux data acquired in 2016 under separate funding as well as acquisition of additional airborne flux data. The latter will be guided by sensitivities identified in the carbon stock and modeling surveys of the UMD prototype system. We will also assess the measurement requirements for airborne flux observations to quantify net carbon emissions and storage. The impact of this project will be to advance the primary CMS goal of evaluation of errors and uncertainties by demonstrating a potentially powerful tool for flux quantification applicable to CMS. We will produce a data set of regional GHG flux estimates and their statistical errors for use in other CMS and community analyses, and we will provide a more comprehensive validation/evaluation of uncertainties in the UMD prototype MRV products. The measurement technique is also potentially applicable to validation for CMS Integrated Emission/Uptake (‘Flux’) products. This research directly addresses the CMS solicitation request to advance remote sensing-based approaches to MRV through use of airborne flux observations as an alternative method for quantifying net carbon emissions, and the need to improve the characterization and quantification of errors and uncertainties in existing NASA CMS products. The work is timely both for maturation of the MRV prototype system to include a better description of uncertainties as well as to make use of a new experimental capability for the corresponding domain. 
Project Associations:
  • CMS
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Land-Atmosphere Flux
  • MRV

Participants:

George (Jim) Collatz, NASA GSFC - retired
Glenn Diskin, NASA Langley Research Center
Thomas Hanisco, NASA GSFC
Reem Hannun, University of Pittsburgh
George Hurtt, University of Maryland
Stephan (Randy) Kawa, NASA GSFC
Paul Newman, NASA GSFC
Glenn Wolfe, NASA GSFC

Project URL(s): None provided.
 
Data
Products:
Product Title:  Regional GHG mixing ratios and flux estimates with their statistical errors
Time Period:  September 2016; May 2017
Description:  The analysis will compare flux data and modeling across gradients of forest height and type as well as soil and climate regime within the US Mid-Atlantic region.
Status:  Public
CMS Science Theme(s):  Land-Atmosphere Flux; MRV
Keywords:  flux, eddy-covariance, carbon dioxide, methane
Spatial Extent:  US Mid-Atlantic region
Spatial Resolution:  1-100 km
Temporal Frequency:  1 Hz
Input Data Products:  NASA Sherpa aircraft navigational data; laboratory instrument calibration data
Algorithm/Models Used:  See Wolfe et al., 2018
Evaluation:  Ongoing comparison with ground based tower flux data
Intercomparison Efforts/Gaps:  Comparison with ground based tower and model fluxes where available
Uncertainty Estimates:  See Wolfe et al., 2018
Uncertainty Categories:  Random, systematic (Wolfe et al., 2018)
Application Areas:  Agricultural moisture, energy, and gas surface flux estimation
Relevant Policies/Programs:  USDA Forest Service Policies/Programs
Potential Users:  CMS community, vegetation process modeling, flux inversion models
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  2
Target Application Readiness Level:  6
Future Developments:  Proposal for further deployment pending; and new paper in review.
Limitations:  Limited coverage in space and time
Date When Product Available:  March 2018
Metadata URL(s):
Data Server URL(s):

https://www-air.larc.nasa.gov/missions/carafe/index.html
Archived Data Citation:  Wolfe, G. M., Kawa, S. R., Hanisco, T. F., Hannun, R. A., Newman, P. A., et al., 2018: The NASA Carbon Airborne Flux Experiment (CARAFE): instrumentation and methodology, Atmos. Meas.

Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

 
Publications: Hannun, R. A., Wolfe, G. M., Kawa, S. R., Hanisco, T. F., Newman, P. A., Alfieri, J. G., Barrick, J., Clark, K. L., DiGangi, J. P., Diskin, G. S., King, J., Kustas, W. P., Mitra, B., Noormets, A., Nowak, J. B., Thornhill, K. L., Vargas, R. 2020. Spatial heterogeneity in CO2, CH4, and energy fluxes: insights from airborne eddy covariance measurements over the Mid-Atlantic region. Environmental Research Letters. 15(3), 035008. DOI: 10.1088/1748-9326/ab7391

Wolfe, G. M., Kawa, S. R., Hanisco, T. F., Hannun, R. A., Newman, P. A., Swanson, A., Bailey, S., Barrick, J., Thornhill, K. L., Diskin, G., DiGangi, J., Nowak, J. B., Sorenson, C., Bland, G., Yungel, J. K., Swenson, C. A. 2018. The NASA Carbon Airborne Flux Experiment (CARAFE): instrumentation and methodology. Atmospheric Measurement Techniques. 11(3), 1757-1776. DOI: 10.5194/amt-11-1757-2018

Archived Data Citations: Wolfe, G. M., Kawa, S. R., Hanisco, T. F., Hannun, R. A., Newman, P. A., et al., 2018: The NASA Carbon Airborne Flux Experiment (CARAFE): instrumentation and methodology, Atmos. Meas.


 

Kennedy (CMS 2015) (2016)
Project Title:Tools to bridge the gap between static CMS maps, models, and stakeholders

Science Team
Members:

Robert Kennedy, Oregon State University (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2015)
Abstract: From its inception, the NASA Carbon Monitoring System (CMS) has largely been organized around two activities: observation-based mapping of biomass and model- based estimation of carbon flux. Although there has been significant progress in both biomass and flux activities at various scales, several challenges hinder the use of biomass products to inform flux modeling. Challenges include: biomass maps are often static or local scale, uncertainties are difficult to render and incorporate into models, and map products are not designed with the needs – and format standards – of modelers in mind. To help address these challenges, we propose a set of research activities organized around two objectives. First, we will develop tools to integrate static and dynamic CMS products of any temporal, spatial, and semantic content into a consistent, continental- U.S.-wide, derived database of yearly land cover, biomass, disturbance and growth in terrestrial systems, along with spatially explicit and consistent uncertainties. These can be used to set states, hone parameters, schedule events, and constrain or benchmark models from which flux estimates ultimately are derived. Second, we will develop a smart application programming interface to allow modelers and stakeholders easy access to these data in the spatial, temporal, and information domain they require. We have assembled a team of Collaborators and Co-Investigators to help guide success. Collaborators include numerous CMS colleagues who have produced or are producing the static or local-scale maps we will integrate into our yearly maps. They will ensure we interpret and use their products appropriately. Co-Investigators include process-level modelers who represent a series of carbon use-cases, ranging from regional scale DGVM implementations to global scale, multi-model ensembles. They will help develop and test the interface to ensure its applicability across a continuum of situations, and will help guide us toward visualization choices appropriate for their stakeholders. Finally, we have engaged key representatives from the Land Processes and Oak Ridge National Lab Distributed Active Archive Centers (LP and ORNL DAACs) to ensure that our interface complements and co-exists with the data access and archiving efforts they continue to lead. Key deliverables include: - A database of 30m resolution, yearly time-step maps from 1990 to present of forest biomass, land cover, tree cover, crop type, and disturbance for the continental U.S., along with uncertainties - Computational interface (API) to allow CMS participants to easily access and analyze that database - Assessment of potential improvement in models derived from these dynamic land surface drivers, including possible reduction in uncertainties. This efforts explicitly addresses the CMS call for follow-on to existing CMS efforts, for development of new remotely-sensed MRV-relevant products, and for improvement of carbon modeling capacity.
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • Decision Support
  • MRV

Participants:

Dominique Bachelet, Oregon State University
Warren Cohen, USDA Forest Service
Michael (Mike) Falkowski, NASA Headquarters
Joshua Fisher, Chapman University
Sangram Ganguly, Rhombus Power Inc.
Andrew (Andy) Hudak, USDA Forest Service
Deborah (Debbie) Huntzinger, Northern Arizona University
David Johnson, USDA
Robert Kennedy, Oregon State University
Thomas (Tom) Maiersperger, USGS, NASA LP DAAC
Sassan Saatchi, Jet Propulsion Laboratory / Caltech
Christopher (Chris) Williams, Clark University
Zhiqiang Yang, USDA Forest Service

Project URL(s): None provided.
 
Data
Products:
Product Title:  Forest biomass, land cover, tree cover, crop type, and disturbance for the continental U.S.: 1990 to present.
Start Date:  01/1990      End Date:  12/2018     (1990=2017)
Description:  
Status:  Public
CMS Science Theme(s):  Land Biomass
Keywords:  Land cover, biomass, Landsat, disturbance
Spatial Extent:  CONUS
Spatial Resolution:  30 m
Temporal Frequency:  annual
Input Data Products:  Landsats 5, 7, 8
Algorithm/Models Used:  Standard reflectance processing on imagery; LandTrendr on Google Earth Engine for temporal segmentation; Spatial-temporal ecological modeling and random forests for mapping
Evaluation:  Cross-validation against original maps
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Standard Deviation of ensemble of random forest trees
Uncertainty Categories:  Ensemble
Application Areas:  Modeling; land surface monitoring (MRV);
Relevant Policies/Programs:  North American Carbon Program (NACP)
Potential Users:  Climate modelers; ecosystem modelers; land use managers (National Forests, protected areas)
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  
Limitations:  Uncertainty estimates and validation limited to time periods of existing extant maps (2001- forward)
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
emapr.ceoas.oregonstate.edu
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-137.25700 East Longitude:-62.03770
North Latitude:53.38630 South Latitude:22.09280

Product Title:  Potential improvement assessment
Start Date:  01/1990      End Date:  12/2018     (annual)
Description:  
Status:  On-going
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; MRV
Keywords:  Modeling
Spatial Extent:  CONUS
Spatial Resolution:  various
Temporal Frequency:  various
Input Data Products:  Dynamic maps generated in project
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  Ensemble
Application Areas:  Flux, prediction
Relevant Policies/Programs:  
Potential Users:  Modelers
Stakeholders:  
Current Application Readiness Level:  7
Start Application Readiness Level:  1
Target Application Readiness Level:  8
Future Developments:  Coordination with modeling partners to ensure utility of map products
Limitations:  Uncertainty estimates and validation limited to time periods of existing extant maps (2001- forward)
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
emapr.ceoas.oregonstate.edu
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-137.25700 East Longitude:-62.03770
North Latitude:53.38630 South Latitude:22.09280

Product Title:  Forest Carbon Stocks and Fluxes from the NFCMS, Conterminous USA, 1990-2010
Start Date:  01/1986      End Date:  12/2010     (1986-01-01 to 2010-12-31 (this period covers the input data))
Description:  This dataset, derived from the National Forest Carbon Monitoring System (NFCMS), provides estimates of forest carbon stocks and fluxes in the form of aboveground woody biomass (AGB), total live biomass, total ecosystem carbon, aboveground coarse woody debris (CWD), and net ecosystem productivity (NEP) as a function of the number of years since the most recent disturbance (i.e., stand age) for forests of the conterminous U.S. at a 30 m resolution for the benchmark years 1990, 2000, and 2010. The data were derived from an inventory-constrained version of the Carnegie-Ames-Stanford Approach (CASA) carbon cycle process model that accounts for disturbance processes for each combination of forest type, site productivity, and pre-disturbance biomass. Also provided are the core model data inputs including the year of the most recent disturbance according to the North American Forest Dynamics (NAFD) and the Monitoring Trends in Burn Severity (MTBS) data products; the type of disturbance; biomass estimates from the year 2000 according to the National Biomass and Carbon Dataset (NBCD); forest-type group; a site productivity classification; and the number of years since stand-replacing disturbance. The data are useful for a wide range of applications including monitoring and reporting recent dynamics of forest carbon across the conterminous U.S., assessment of recent trends with attribution to disturbance and regrowth drivers, conservation planning, and assessment of climate change mitigation opportunities within the forest sector.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  Conterminous U.S. divided into nine regions
Spatial Resolution:  30 m
Temporal Frequency:  Annual data for the selected years of 1990, 2000, and 2010
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1829
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1829
Archived Data Citation:  Williams, C.A., N. Hasler, H. Gu, and Y. Zhou. 2020. Forest Carbon Stocks and Fluxes from the NFCMS, Conterminous USA, 1990-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1829

Bounding Coordinates:
West Longitude:-127.69000 East Longitude:-65.73000
North Latitude:50.37000 South Latitude:23.19000

 
Publications: Hurtt, G. C., Andrews, A., Bowman, K., Brown, M. E., Chatterjee, A., Escobar, V., Fatoyinbo, L., Griffith, P., Guy, M., Healey, S. P., Jacob, D. J., Kennedy, R., Lohrenz, S., McGroddy, M. E., Morales, V., Nehrkorn, T., Ott, L., Saatchi, S., Sepulveda Carlo, E., Serbin, S. P., Tian, H. 2022. The NASA Carbon Monitoring System Phase 2 synthesis: scope, findings, gaps and recommended next steps. Environmental Research Letters. 17(6), 063010. DOI: 10.1088/1748-9326/ac7407

Kennedy, R., Yang, Z., Gorelick, N., Braaten, J., Cavalcante, L., Cohen, W., Healey, S. 2018. Implementation of the LandTrendr Algorithm on Google Earth Engine. Remote Sensing. 10(5), 691. DOI: 10.3390/rs10050691

Liu, Y., Piao, S., Gasser, T., Ciais, P., Yang, H., Wang, H., Keenan, T. F., Huang, M., Wan, S., Song, J., Wang, K., Janssens, I. A., Penuelas, J., Huntingford, C., Wang, X., Altaf Arain, M., Fang, Y., Fisher, J. B., Huang, M., Huntzinger, D. N., Ito, A., Jain, A. K., Mao, J., Michalak, A. M., Peng, C., Poulter, B., Schwalm, C., Shi, X., Tian, H., Wei, Y., Zeng, N., Zhu, Q., Wang, T. 2019. Field-experiment constraints on the enhancement of the terrestrial carbon sink by CO2 fertilization. Nature Geoscience. 12(10), 809-814. DOI: 10.1038/s41561-019-0436-1

Schwalm, C. R., Huntzinger, D. N., Michalak, A. M., Schaefer, K., Fisher, J. B., Fang, Y., Wei, Y. 2020. Modeling suggests fossil fuel emissions have been driving increased land carbon uptake since the turn of the 20th Century. Scientific Reports. 10(1). DOI: 10.1038/s41598-020-66103-9

Schwalm, C. R., Schaefer, K., Fisher, J. B., Huntzinger, D., Elshorbany, Y., Fang, Y., Hayes, D., Jafarov, E., Michalak, A. M., Piper, M., Stofferahn, E., Wang, K., Wei, Y. 2019. Divergence in land surface modeling: linking spread to structure. Environmental Research Communications. 1(11), 111004. DOI: 10.1088/2515-7620/ab4a8a

Williams, C. A., Gu, H., Jiao, T. 2021. Climate impacts of U.S. forest loss span net warming to net cooling. Science Advances. 7(7). DOI: 10.1126/sciadv.aax8859

Zhou, Y., Williams, C. A., Hasler, N., Gu, H., Kennedy, R. 2021. Beyond biomass to carbon fluxes: application and evaluation of a comprehensive forest carbon monitoring system. Environmental Research Letters. 16(5), 055026. DOI: 10.1088/1748-9326/abf06d

Archived Data Citations: Williams, C.A., N. Hasler, H. Gu, and Y. Zhou. 2020. Forest Carbon Stocks and Fluxes from the NFCMS, Conterminous USA, 1990-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1829


 

Lin (CMS 2015) (2016)
Project Title:Towards a Complex Terrain Carbon Monitoring System (CMS-Mountains): Development and Testing in the Western U.S.

Science Team
Members:

John Lin, University of Utah (Project Lead)
Brett Raczka, NCAR

Solicitation:NASA: Carbon Monitoring System (2015)
Successor Projects: Lin (CMS 2018)  
Abstract: Despite the need to understand terrestrial biospheric carbon fluxes to account for carbon cycle feedbacks and predict future CO2 concentrations, knowledge of these fluxes at the regional scale remains poor. This is particularly true in mountainous areas, where complex atmospheric flows and relative lack of observations lead to significant uncertainties in carbon fluxes. Yet many mountainous regions also have significant forest cover and biomass—i.e., they are areas with the potential to serve as terrestrial carbon sinks. However, these sinks are highly dynamic and vulnerable to disturbance events, such as drought, insect damage, and wildfires. A strong need exists for the use of satellite remote sensing and modeling to help shed light on carbon dynamics in regions of complex terrain. Recent remote sensing advances from NASA can now be used to address the observational gap in mountainous areas. First, column-averaged CO2 (XCO2) yields atmospheric constraints on modeled biospheric fluxes in regions where in-situ CO2 observations are absent. Second, retrieval of Solar-Induced Fluorescence (SIF) from space has provided a powerful means to sense physiological signals of gross primary productivity (GPP) at regional to global scales. However, the relationship between SIF and GPP is complicated, and current uncertainties prevent scaling of well-established leaf-level fluorescence mechanisms to interpret GPP at larger scales, especially for coniferous species. Our proposed research will address the following key scientific questions: 1) How can satellite, atmospheric in-situ, and ecological observations be combined with atmospheric and biospheric models to inform carbon budgets in regions of complex terrain? 2) How is satellite-retrieved SIF related to leaf-level physiology? 3) What are the impacts of drought on carbon cycling in mountainous regions? We propose development and testing of a new Carbon Monitoring System over Mountains (CMS-Mountains) covering the Western U.S., where we will leverage numerous existing efforts in biospheric and atmospheric modeling. We will run the Community Land Model (CLM) at high spatial resolution, assimilating satellite observations of SIF, leaf area index, and snow cover within the Data Assimilation Research Testbed (DART). Signals of simulated biospheric fluxes from CLM-DART will be compared via atmospheric modeling to remotely sensed XCO2. Discrepancies will be minimized through adjustment of the regional fluxes as part of an atmospheric inversion. In this way, CMS-Mountains will deliver estimates of regional scale carbon fluxes over the Western U.S., along with their uncertainties, constrained by remotely sensed datasets. While the proposed project will focus on the Western U.S., the framework we develop will be applicable elsewhere. We anticipate the CMS-Mountains platform will ultimately be applied to other regions of complex terrain around the world, driven by remote sensing data in the absence of in-situ measurements. This project directly addresses the objectives of NASA’s CMS program, as mentioned in the proposal call. We are proposing a study that uses “remote sensing data products to produce and evaluate prototype MRV system approaches”. It will contribute towards “U.S. national efforts toward integrated carbon monitoring” by helping to constrain the U.S. carbon budget for a region that is poorly understood (Western U.S.). Moreover, our project will help “improve the characterization and quantification of errors and uncertainties in existing and/or proposed NASA CMS products” for regions of complex terrain. To our knowledge, existing CMS projects either have a global scope or focus on regions outside of mountainous areas. By focusing on the carbon budget in the Western U.S., an area of complex terrain, our project will help quantify the magnitude and sources of uncertainties in other CMS products over this area.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Atmospheric Transport
  • Land-Atmosphere Flux
  • MRV

Participants:

Jeffrey Anderson, NCAR
Arlyn Andrews, NOAA Earth System Research Laboratory
David Bowling, University of Utah
Henrique Duarte, University of Utah
Christian Frankenberg, Caltech
Charles Koven, Lawrence Berkeley National Laboratory
Ming Li, University of Utah
John Lin, University of Utah
Brett Raczka, NCAR

Project URL(s): None provided.
 
Data
Products:
Product Title:  Source code for SIF simulations at Niwot Ridge
Description:  This source code was used to perform the SIF simulations described in Raczka et al., (2019) JGR-Biogeosciences. The three formulation are CLM-SIF, CLM-SIF-NPQ and CLM-SIF-NPQ-Kr.

**IMPORTANT: CLM-SIF was designed for general use (multi-site/regional/global simulations) -no calibration specific to Niwot Ridge. CLM-SIF-NPQ and CLM-SIF-NPQ-Kr include parameterizations specific to Niwot Ridge site simulations, not designed for general use.

Solar induced fluorescence description for each model formulation:

CLM-SIF: Adopted from Lee et al., (2015), adds the impact of nitrogen limitation on Ja. Uses Flexas et al., (2002) data to parameterize reversible NPQ.

CLM-SIF-NPQ: Includes representation of both sustained and reversible NPQ. Sustained NPQ based upon acclimation model of temperature. Both sustained and reversible NPQ uses PAM fluorometry observations taken at Hyytiala, Finland, and adopted to Niwot Ridge Colorado.

CLM-SIF-NPQ-Kr: Similar to above but uses seasonal varying representation of reversible NPQ.

Note: This source code based off CESM1.2 release of CLM4.5 URL: https://svn-ccsm-models.cgd.ucar.edu/cesm1/release_tags/cesm1_2_1 Repository Root: https://svn-ccsm-models.cgd.ucar.edu Repository UUID: fe37f545-8307-0410-aea5-b40df96820b5 Revision: 62904
Status:  Public
CMS Science Theme(s):  
Keywords:  
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
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Relevant Policies/Programs:  
Potential Users:  
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Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  1
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):

https://github.com/braczka/sustained_NPQ
Data Server URL(s):

https://github.com/braczka/sustained_NPQ
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Initial estimates of regional scale carbon fluxes and stocks over the Western U.S.
Time Period:  2000-2018
Description:  Above-ground biomass (AGB), gross primary production (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) simulated by the Community Land Model (CLM Version 4.5) over the Western U.S. after initial calibration of model parameters
Status:  Preliminary
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Carbon fluxes; carbon stocks; CLM
Spatial Extent:  Western U.S.
Spatial Resolution:  0.5 x 0.5 deg
Temporal Frequency:  3 hourly
Input Data Products:  CRU-NCEP meteorological forcing (alternative products will be tested; extension from 2010 is needed); Surface data maps from the CESM/CLM distribution
Algorithm/Models Used:  Community Land Model (CLM Version 4.5)
Evaluation:  Available AGB products (e.g., Kellndorfer et al. 2013), MODIS LAI product (De Kauwe 2011), FLUXNET-MTE product (Jung et al. 2009; 2010)
Intercomparison Efforts/Gaps:  Datasets from MIPs (e.g., MsTMIP)
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  GHG Inventory
Relevant Policies/Programs:  US National Greenhouse Gas Inventory (NGHGI), Clean Air Act (CAA), U.S. Carbon Cycle Science Program (USCCSP), North American Carbon Program (NACP)
Potential Users:  Land surface modeling community; NACP community; USDA Forest Service; flux tower community
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  1
Future Developments:  Presentations at CMS and AGU conferences
Limitations:  Unknown at present
Date When Product Available:  Summer 2019
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-130.00000 East Longitude:-100.00000
North Latitude:50.00000 South Latitude:26.00000

Product Title:  CLM Simulated Solar-Induced Fluorescence, Niwot Ridge, Colorado, USA, 1998-2018
Start Date:  01/1998      End Date:  01/2019     (1998-2018)
Description:  This dataset provides results for simulations of solar-induced chlorophyll fluorescence (SIF) implemented within the terrestrial biosphere Community Land Model (CLM 4.5) for Niwot Ridge, Colorado, USA, from 1998-2018. The data include outputs from three model simulations designed to test the importance of non-photochemical quenching (NPQ), that is, the absorbed light energy dissipated as heat, in determining seasonal SIF.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  sink, source, flux/movement
Spatial Extent:  Niwot Ridge AmeriFlux tower
Spatial Resolution:  
Temporal Frequency:  Hourly
Input Data Products:  Flux tower meteorology, atmospheric CO2, land surface, soil and vegetation characteristics
Algorithm/Models Used:  Community Land Model (CLM 4.5); SCOPE – forest canopy model
Evaluation:  Remotely sensed SIF (e.g. GOME, OCO2); Ameriflux tower observations
Intercomparison Efforts/Gaps:  Literature
Uncertainty Estimates:  Multiple model runs perturbing key SIF parameters
Uncertainty Categories:  Ensemble
Application Areas:  Calibration of SIF-enabled CLM 4.5 in preparation for regional simulation of Western US
Relevant Policies/Programs:  US National Greenhouse Gas Inventory (NGHGI), Clean Air Act (CAA), U.S. Carbon Cycle Science Program (USCCSP), North American Carbon Program (NACP)
Potential Users:  SIF researchers, flux tower community, USDA Forest Service, Land surface modeling community, NACP community
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  1
Future Developments:  Presentations at CMS and AGU conferences
Limitations:  Unknown at present
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1720
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1720
Archived Data Citation:  Raczka, B.M., A. Porcar-Castell, T. Magney, J. Lee, P. Kohler, C. Frankenberg, K. Grossmann, B.A. Logan, J. Stutz, P.D. Blanken, S.P. Burns, H.F. Duarte, X. Yang, J.C. Lin, and D.R. Bowling. 2019. CLM Simulated Solar-Induced Fluorescence, Niwot Ridge, Colorado, USA, 1998-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1720

Bounding Coordinates:
West Longitude:-105.54640 East Longitude:-105.54639
North Latitude:40.03291 South Latitude:40.03290

Product Title:  Conifer Needle Chlorophyll Fluorescence, Niwot Ridge, Colorado, USA, 2017-2018
Start Date:  07/2017      End Date:  06/2018
Description:  This dataset provides chlorophyll fluorescence measurements made on pine and spruce needle tissues at the Niwot Ridge AmeriFlux Core site (US-NR1) near Nederland, Colorado, USA, during the summers of 2017 and 2018. Two types of measurements were made using pulse-amplitude-modulation (PAM) fluorometry: the photosystem II (PSII) operating efficiency in the light (Fq'/Fm' at variable light levels), and the maximum quantum efficiency of PSII photochemistry (Fv/Fm) on dark-acclimated tissues. Chlorophyll fluorescence measurements were made to determine seasonality of photosynthetic performance at the needle level.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Niwot Ridge AmeriFlux Core tower, Colorado
Spatial Resolution:  branch level measurements
Temporal Frequency:  Monthly
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  1
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1722
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1722
Archived Data Citation:  Bowling, D.R., and B.A. Logan. 2019. Conifer Needle Chlorophyll Fluorescence, Niwot Ridge, Colorado, USA, 2017-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1722

Bounding Coordinates:
West Longitude:-105.55000 East Longitude:-105.54000
North Latitude:40.03500 South Latitude:40.03000

Product Title:  Conifer Needle Pigment Composition, Niwot Ridge, Colorado, USA, 2017-2018
Start Date:  07/2017      End Date:  06/2018
Description:  This dataset provides concentrations of pigments in pine and spruce needle tissues collected at the Niwot Ridge AmeriFlux Core site (US-NR1) near Nederland, Colorado, USA, during the summers of 2017 and 2018. Pigments measured included Chlorophyll A and B, Violaxanthin, Antheraxanthin, Zeaxanthin, Neoxanthin, Lutein, and beta-Carotene. Measurements were made on sun foliage from two canopy-access towers near the main flux tower, and in the laboratory on branches collected from those towers, every 4-8 weeks over the annual cycle. Due to canopy structure, a limited number of trees were accessible from the towers, preventing extensive replication. Pigments were extracted in acetone and analyzed by HPLC. The measurements were made to evaluate seasonal changes associated with the down-regulation of photosynthesis.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Niwot Ridge AmeriFlux Core tower, Colorado
Spatial Resolution:  branch level measurements
Temporal Frequency:  Approximately monthly
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  1
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1723
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1723
Archived Data Citation:  Bowling, D.R., and B.A. Logan. 2019. Conifer Needle Pigment Composition, Niwot Ridge, Colorado, USA, 2017-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1723

Bounding Coordinates:
West Longitude:-105.55000 East Longitude:-105.54000
North Latitude:40.03500 South Latitude:40.03000

Product Title:  CLM5-DART Regional Carbon Fluxes and Stocks over the Western US, 1998-2010
Start Date:  01/1998      End Date:  12/2010     (1998-2010)
Description:  This dataset provides monthly estimates of biomass stocks and land-atmosphere carbon exchange across the western United States at 0.95 degrees longitude x 1.25 degrees latitude grid resolution from 1998 through 2010. The data include outputs from two types of model simulations: (1) a "free" simulation which used Community Land Model (CLM5.0) simulations forced with meteorology appropriate for complex mountainous terrain, and (2) "assimilation" runs using the land surface data assimilation system (CLM5-DART). In assimilation runs, the CLM5 vegetation state is constrained by remotely sensed observations of leaf area index and aboveground biomass, which influenced biomass stocks and carbon fluxes.
Status:  Archived
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux
Keywords:  Carbon fluxes; carbon stocks; CLM; data assimilation; DART
Spatial Extent:  Western U.S.
Spatial Resolution:  0.95 to 1.25 degrees
Temporal Frequency:  monthly
Input Data Products:  Meteorological forcing (ensemble dataset to be determined); surface data maps from the CESM/CLM distribution; satellite observations of SIF (OCO-2, GOME-2), leaf area index (TERRA/MODIS), and snow cover (TERRA/MODIS) to be assimilated within DART
Algorithm/Models Used:  Community Land Model (CLM Version 4.5) and Data Assimilation Research Testbed (DART)
Evaluation:  Available AGB and flux products
Intercomparison Efforts/Gaps:  Datasets from MIPs
Uncertainty Estimates:  Via DART
Uncertainty Categories:  Ensemble
Application Areas:  GHG Inventory
Relevant Policies/Programs:  US National Greenhouse Gas Inventory (NGHGI), Clean Air Act (CAA), U.S. Carbon Cycle Science Program (USCCSP), North American Carbon Program (NACP)
Potential Users:  Land surface modeling community; NACP community; USDA Forest Service; flux tower community
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  1
Future Developments:  Presentations at CMS and AGU conferences
Limitations:  Unknown at present
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1856
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1856
Archived Data Citation:  Raczka, B.M., T.J. Hoar, H.F. Duarte, A.M. Fox, J.L. Anderson, D.R. Bowling, and J.C. Lin. 2021. CLM5-DART Regional Carbon Fluxes and Stocks over the Western US, 1998-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1856

Bounding Coordinates:
West Longitude:-130.62000 East Longitude:-99.38000
North Latitude:50.89000 South Latitude:25.44000

 
Publications: Kannenberg, S. A., Bowling, D. R., Anderegg, W. R. L. 2020. Hot moments in ecosystem fluxes: High GPP anomalies exert outsized influence on the carbon cycle and are differentially driven by moisture availability across biomes. Environmental Research Letters. 15(5), 054004. DOI: 10.1088/1748-9326/ab7b97

Magney, T. S., Bowling, D. R., Logan, B. A., Grossmann, K., Stutz, J., Blanken, P. D., Burns, S. P., Cheng, R., Garcia, M. A., Kohler, P., Lopez, S., Parazoo, N. C., Raczka, B., Schimel, D., Frankenberg, C. 2019. Mechanistic evidence for tracking the seasonality of photosynthesis with solar-induced fluorescence. Proceedings of the National Academy of Sciences. 116(24), 11640-11645. DOI: 10.1073/pnas.1900278116

Peters, W., van der Velde, I. R., van Schaik, E., Miller, J. B., Ciais, P., Duarte, H. F., van der Laan-Luijkx, I. T., van der Molen, M. K., Scholze, M., Schaefer, K., Vidale, P. L., Verhoef, A., Warlind, D., Zhu, D., Tans, P. P., Vaughn, B., White, J. W. C. 2018. Increased water-use efficiency and reduced CO2 uptake by plants during droughts at a continental scale. Nature Geoscience. 11(10), 744-748. DOI: 10.1038/s41561-018-0212-7

Raczka, B., Hoar, T. J., Duarte, H. F., Fox, A. M., Anderson, J. L., Bowling, D. R., Lin, J. C. 2021. Improving CLM5.0 Biomass and Carbon Exchange Across the Western United States Using a Data Assimilation System. Journal of Advances in Modeling Earth Systems. 13(7). DOI: 10.1029/2020MS002421

Raczka, B., Porcar-Castell, A., Magney, T., Lee, J. E., Kohler, P., Frankenberg, C., Grossmann, K., Logan, B. A., Stutz, J., Blanken, P. D., Burns, S. P., Duarte, H., Yang, X., Lin, J. C., Bowling, D. R. 2019. Sustained Nonphotochemical Quenching Shapes the Seasonal Pattern of Solar-Induced Fluorescence at a High-Elevation Evergreen Forest. Journal of Geophysical Research: Biogeosciences. 124(7), 2005-2020. DOI: 10.1029/2018JG004883

Zuromski, L. M., Bowling, D. R., Kohler, P., Frankenberg, C., Goulden, M. L., Blanken, P. D., Lin, J. C. 2018. Solar-Induced Fluorescence Detects Interannual Variation in Gross Primary Production of Coniferous Forests in the Western United States. Geophysical Research Letters. 45(14), 7184-7193. DOI: 10.1029/2018GL077906

Archived Data Citations: Raczka, B.M., A. Porcar-Castell, T. Magney, J. Lee, P. Kohler, C. Frankenberg, K. Grossmann, B.A. Logan, J. Stutz, P.D. Blanken, S.P. Burns, H.F. Duarte, X. Yang, J.C. Lin, and D.R. Bowling. 2019. CLM Simulated Solar-Induced Fluorescence, Niwot Ridge, Colorado, USA, 1998-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1720

Raczka, B.M., T.J. Hoar, H.F. Duarte, A.M. Fox, J.L. Anderson, D.R. Bowling, and J.C. Lin. 2021. CLM5-DART Regional Carbon Fluxes and Stocks over the Western US, 1998-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1856

Bowling, D.R., and B.A. Logan. 2019. Conifer Needle Pigment Composition, Niwot Ridge, Colorado, USA, 2017-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1723

Bowling, D.R., and B.A. Logan. 2019. Conifer Needle Chlorophyll Fluorescence, Niwot Ridge, Colorado, USA, 2017-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1722


 

Miller (CMS 2015) (2016)
Project Title:Disaggregating Amazon Basin fire fluxes using remote sensing of atmospheric carbon monoxide and burned area

Science Team
Members:

John Miller, NOAA Global Monitoring Laboratory (Project Lead)
Sourish Basu, NASA GSFC GMAO / University of Maryland

Solicitation:NASA: Carbon Monitoring System (2015)
Abstract: We propose to use the combination of remote sensing of atmospheric carbon monoxide (CO) from three different satellite sensors -- MOPITT, IASI and TROPOMI -- along with state of the art, high resolution, maps of burned area to determine fire emissions over the Amazon Basin, spatially, temporally, and by fire type. These data will be used with a data assimilation system that will appropriately scale burned area maps to match both in situ and satellite CO data. Calculating emissions from different fire types will allow us to better understand the net climate impact of fire emissions in the Amazon Basin (note that not all fire emission have a net climate impact). Note that while fire emission modeling approaches based on burned area, like CASA/GFED also calculate fire by type and region, they are based on coarser land surface maps. They also likely underestimate understory fires have trouble identifying fires during high aerosol loading and persistent cloud cover. In contrast, an atmospheric approach, based on measurements of CO and high resolution burned area maps, will allow for integration of carbon emissions from various types of fires, whether or not they can be easily detected from space. Fire carbon emission by type and area will be a valuable addition to existing methods used to calculate forest carbon emissions as part of REDD (Reducing Emissions from Deforestation and forest Degradation) projects. To this end, we will also conduct a stakeholders workshop involving Brazilian scientists and climate policy representatives to communicate our results and approach and learn about their information needs. The policy-relevant scientific research and stakeholder outreach we propose are both closely aligned with the goals of NASA’s Carbon Monitoring System (CMS). Specific project deliverables proposed include development of novel burned area products at high resolution from 2010-2018 that will allow for improved classification of burned area and inclusion of hard to detect fires, such as understory fires, in burned area maps. On the atmospheric side, we will conduct a thorough bias assessment of the satellite data using in situ CO data, allowing us to apply bias correction algorithms. Bias corrections are critical to ensure that gradients in the spatially dense CO data are geophysical and do not result in flux biases. Moreover, bias corrected satellite CO products will be made available to the broader community.
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Land-Atmosphere Flux
  • MRV

Participants:

Ilse Aben, SRON Netherlands Institute for Space Research
Arlyn Andrews, NOAA Earth System Research Laboratory
Sourish Basu, NASA GSFC GMAO / University of Maryland
Martine De Mazière, Royal Belgian Institute for Space Aeronomy
Merritt Deeter, National Center for Atmospheric Research
Jost Lavric, Acoem Ecotech
John Miller, NOAA Global Monitoring Laboratory
Douglas (Doug) Morton, NASA GSFC
Jean Ometto, National Institute for Space Research
Rodrigo Augusto Ferreira Souza, State University of Amazonas
Thijs Thomas Van Leeuwen, VanderSat B.V.

Project URL(s): None provided.
 
Data
Products:
Product Title:  Bias assessment of the satellite data using in situ CO data, allowing us to apply bias correction algorithms
Description:  Bias corrections are critical to ensure that gradients in the spatially dense CO data are geophysical and do not result in flux biases. Moreover, bias corrected satellite CO products will be made available to the broader community.
Status:  Planned
CMS Science Theme(s):  Land-Atmosphere Flux; MRV
Keywords:  
Spatial Extent:  Amazon Basin
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  Atmospheric carbon monoxide (CO) from MOPITT, IASI and TROPOMI; high resolution, maps of burned area
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  REDD+
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  We will conduct a stakeholders workshop involving Brazilian scientists and climate policy representatives to communicate our results and approach and learn about their information needs.
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

Product Title:  Development of novel burned area products at high resolution
Time Period:  2010-2018
Description:  
Status:  Planned
CMS Science Theme(s):  Land-Atmosphere Flux; MRV
Keywords:  
Spatial Extent:  Amazon Basin
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  Atmospheric carbon monoxide (CO) from MOPITT, IASI and TROPOMI; high resolution, maps of burned area
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  REDD+
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  We will conduct a stakeholders workshop involving Brazilian scientists and climate policy representatives to communicate our results and approach and learn about their information needs.
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

Product Title:  Fire emissions over the Amazon Basin, spatially, temporally, and by fire type
Description:  
Status:  Planned
CMS Science Theme(s):  Land-Atmosphere Flux; MRV
Keywords:  
Spatial Extent:  Amazon Basin
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  Atmospheric carbon monoxide (CO) from MOPITT, IASI and TROPOMI; high resolution, maps of burned area
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  REDD+
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  We will conduct a stakeholders workshop involving Brazilian scientists and climate policy representatives to communicate our results and approach and learn about their information needs.
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

 
Publications: None provided.


 

Nehrkorn (CMS 2015) (2016)
Project Title:Prototype regional carbon monitoring systems for urban regions

Science Team
Members:

Thomas Nehrkorn, AER, Inc (Project Lead)
Lucy Hutyra, Boston University
Steven (Steve) Wofsy, Harvard University

Solicitation:NASA: Carbon Monitoring System (2015)
Precursor Projects: Nehrkorn (CMS 2013)  
Abstract: The 2015 COP21 meeting in Paris fundamentally changed the approach to carbon monitoring, reporting, verification and validation (MRV/MRVV). The emphasis on voluntary measures, and the large number of ongoing GHG reduction efforts at sub- national levels in government, non-profit, and private sectors, require monitoring capability at policy-relevant scales: region, state, and city. Urban regions are particularly important because cities account for more than 70% of all global fossil-fuel CO2 emissions, and urban losses of natural gas CH4 equal or exceed emissions from production and processing. We propose research to develop a prototype MRV system for Boston and the urban Northeastern US, leveraging results of our current CMS project. We will advance our framework and help deploy a similar system in the San Francisco Bay Area, collaborating with the Bay Area Air Quality Management District (BAAQMD). Both cities have strong GHG reduction efforts (Boston's plan was honored at COP21, and the BAAQMD has ambitious GHG reduction goals for their 10-point Climate Action Work Program). We propose new or enhanced capabilities in four key areas: (1) observational networks that  ground-based remote sensing from new solar-viewing spectrometers and Lidar with observations from space-borne platforms (OCO-2, OCO-3, TROPOMI, and CALIPSO) and in situ networks; (2) novel bottom-up approaches to generate high- resolution flux inventories in urban and surrounding areas; (3) a high-resolution transport modeling (WRF-STILT) framework, coupled to inversion algorithms to provide posterior estimates of fluxes and uncertainties on scales from urban region to neighborhood; and (4) strong engagement with stakeholder communities and local and state entities. Quantification and reduction of uncertainties are a key focus. We assess bottom-up inventories by comparing with independent estimates; verify meteorological fields used for transport modeling against a wide range of observations; and undertake intensive field studies to quantify systematic errors in emissions estimates. The San Francisco Bay area and Boston have contrasting meteorological (e.g., marine vs. continental inflow) and biophysical characteristics (e.g., biomes, seasonality, topographical heterogeneity). We plan an intensive study in the Bay Area under auspices of the BAAQMD, and will focus on transferring to the District methods we have developed for bottom-up inventories at high resolution and elements of our network design and analysis. This work will help us to apply our techniques and findings from the Northeast to elsewhere in the US and the world. We will assess the MRV capability of column-integrated measurements, both from new ground-based FTS instruments, and space-borne platforms (OCO-2 and OCO-3). Our transport modeling framework will take advantage of recent advances in the treatment of near-field emissions and high-resolution modeling for urban areas. Our proposed bottom- up inventory approach for anthropogenic emissions leverages working relationships with stakeholders to enable use of non-standard activity data, and it treats previously neglected sectors (urban biosphere, human respiration) needed to interpret observational data. We plan to widen stakeholder interactions and address user needs by involving interested parties through exposure to pilot data products and methods transfer. Our proposal addresses core goals of the NNH15ZDA001N-CMS solicitation: 'using remote sensing data products to produce and evaluate prototype MRV system approaches' and 'studies to improve the characterization and quantification of errors and uncertainties [...] in the algorithms, models, and associated methodologies', and 'studies of stakeholder interests and requirements'. The proposed work will benefit from the team's involvement with the OCO-2 Science Team, the Environmental Defense Fund Methane Initiative, and the CMS project led by Dr. A. Andrews.
Measurement Approaches:
  • Remote Sensing
  • Airborne Sampling
  • Tall Tower Measurements
  • In Situ Measurements
  • Modeling
  • Synthesis
Project Associations:
  • CMS
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Atmospheric Transport
  • Land-Atmosphere Flux
  • MRV

Participants:

Bill Callahan, Earth Networks
Jia Chen, Technical University of Munich
Hong-Hanh Chu, Massachusetts Executive Office of Energy & Environmental Affairs
Cutler Cleveland, Boston University Institute for Sustainable Energy (and Carbon Free Boston Initiative)
Peter Fox-Penner, Boston University Institute for Sustainable Energy (and Carbon Free Boston Initiative)
Abhinav Guha, Bay Area Air Quality Management District
Vineet Gupta, City of Boston, Boston Transportation Department
Steven Hamburg, Environmental Defense Fund
Lucy Hutyra, Boston University
Thomas Nehrkorn, AER, Inc
Chris Osgood, City of Boston, Office of New Urban Mechanics
Scott Peterson, Boston Metropolitan Planning Organization
Andrew Reinmann, Boston University
Joe Rudek, Environmental Defense Fund
Maryann Sargent, Harvard University
Steven (Steve) Wofsy, Harvard University

Project URL(s): None provided.
 
Data
Products:
Product Title:  CMS: CO2 Emissions from Fossil Fuels Combustion, ACES Inventory for Northeastern USA
Start Date:  01/2011      End Date:  12/2014     (mid-2013 to present)
Description:  This dataset provides estimates of annual and hourly carbon dioxide (CO2) emissions from the combustion of fossil fuels (FF) for 13 states across the Northeastern United States. The Anthropogenic Carbon Emissions System (ACES) was used to estimate annual FFCO2 emissions for nine different emissions source sectors on a 1 x 1 km spatial grid, for the year 2011. Hourly estimates of FFCO2 for the years 2013 and 2014 were derived from the 2011 annual emissions by holding the total emissions constant, but accounting for seasonal and daily variations in meteorology, fuel consumption, and traffic patterns across these two years.
Status:  Archived
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux; MRV
Keywords:  
Spatial Extent:  Boston-DC urban corridor
Spatial Resolution:  1 km
Temporal Frequency:  Hourly
Input Data Products:  in-situ and remote CO2 observation and methane observations; a priori anthropogenic and biospheric flux estimates and related data
Algorithm/Models Used:  VPRM biosphere model; inversion for posterior flux estimate
Evaluation:  Internal QA/QC and consistency checks
Intercomparison Efforts/Gaps:  Posterior flux estimates will be compared against available CMS flux products
Uncertainty Estimates:  Prior flux uncertainties based primarily on model inter-comparisons; posterior fluxes take into account transport and inversion uncertainties and posterior covariance estimates from inversion
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  MRV; GHG emissions inventory
Relevant Policies/Programs:  RGGI, C40 Cities Climate Leadership Group, ICLEI Local Governments for Sustainability, FLPMA, CAA
Potential Users:  OCO-2 Science Team, CMS Arlyn Andrews
Stakeholders:  Boston University (Point of Contact: Peter Fox-Penner, pfoxp@bu.edu); Central Transportation Planning Staff (Boston Metropolitan Planning Organization) (Point of Contact: Scott Peterson, speterson@ctps.org); City of Boston, Boston Transportation Department (Point of Contact: Vineet Gupta, vineet.gupta@boston.gov); City of Boston, Office of New Urban Mechanics (Point of Contact: Chris Osgood, chris.osgood@boston.gov); Multiple Metropolitan Planning Organizations and other planning agencies across the U.S. (Point of Contact: Various contacts); Science community (Point of Contact: Various contacts); State of Massachusetts - Greenhouse Gas Emissions Reporting Program (Point of Contact: Hong-Hanh Chu, hong-hanh.chu@state.ma.us)
Current Application Readiness Level:  3
Start Application Readiness Level:  1
Target Application Readiness Level:  3
Future Developments:  
Limitations:  
Date When Product Available:  2018-04-19
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://daac.ornl.gov/CMS/guides/CMS_Carbon_Emissions_NE_US.html
Data Server URL(s):

https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1501
Archived Data Citation:  Gately, C., and L.R. Hutyra. 2018. CMS: CO2 Emissions from Fossil Fuels Combustion, ACES Inventory for Northeastern USA. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1501

Bounding Coordinates:
West Longitude:-81.78000 East Longitude:-65.93000
North Latitude:49.19000 South Latitude:34.51000

Product Title:  High-resolution flux inventories in San Francisco Bay Area
Time Period:  2015 to present
Description:  Flux estimates of CO2 and Methane
Status:  Planned
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux; MRV
Keywords:  
Spatial Extent:  San Francisco Bay Area
Spatial Resolution:  1 km
Temporal Frequency:  Hourly
Input Data Products:  in-situ and remote CO2 observation and methane observations; a priori anthropogenic and biospheric flux estimates and related data
Algorithm/Models Used:  VPRM biosphere model; inversion for posterior flux estimate
Evaluation:  Internal QA/QC and consistency checks
Intercomparison Efforts/Gaps:  Posterior flux estimates will be compared against available CMS flux products
Uncertainty Estimates:  Prior flux uncertainties based primarily on model inter-comparisons; posterior fluxes take into account transport and inversion uncertainties and posterior covariance estimates from inversion
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  MRV; GHG emissions inventory
Relevant Policies/Programs:  CARB, C40 Cities Climate Leadership Group, ICLEI Local Governments for Sustainability
Potential Users:  Bay Area Air Quality Management District (BAAQMD), OCO-2 Science Team, Environmental Defense Fund Methane Initiative, CMS Arlyn Andrews
Stakeholders:  Bay Area Air Quality Management District (BAAQMD) (Point of Contact: Dr. Abhinav Guha (aguha@baaqmd.gov))
Current Application Readiness Level:  3
Start Application Readiness Level:  1
Target Application Readiness Level:  3
Future Developments:  
Limitations:  
Date When Product Available:  December 2018
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-122.63000 East Longitude:-121.63000
North Latitude:37.87000 South Latitude:37.37000

Product Title:  WRF-STILT Gridded Footprints for Boston, MA, USA, 2013-2014
Start Date:  07/2013      End Date:  12/2014     (mid-2013 to present)
Description:  This dataset provides Weather Research and Forecasting (WRF) Stochastic Time-Inverted Lagrangian Transport (STILT) footprint data products for two receptors located in Boston, Massachusetts, USA, for July 2013 - December 2014. The data are gridded footprints on a 1-km grid congruent with the ACES emissions inventory. Meteorological fields from version 3.5.1 of the Weather Research and Forecasting model are used to drive STILT. STILT applies a Lagrangian particle dispersion model backwards in time from a measurement location (the "receptor" location), to create the adjoint of the transport model in the form of a "footprint" field. The footprint, with units of mixing ratio, quantifies the influence of upwind surface fluxes on CO2 and CH4 concentrations measured at the receptor and is computed by counting the number of particles in a surface-influenced volume and the time spent in that volume.
Status:  Archived
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux; MRV
Keywords:  
Spatial Extent:  Boston, urban Northeastern U.S.
Spatial Resolution:  1 km
Temporal Frequency:  Hourly
Input Data Products:  NARR, MURSST, prepBUFR and ACARS observations
Algorithm/Models Used:  WRF-STILT
Evaluation:  WRF-MET evaluation against available observations
Intercomparison Efforts/Gaps:  Comparison against NAM-HYSPLIT
Uncertainty Estimates:  Comparison against NAM-HYSPLIT and WRF-MET evaluation
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  MRV; GHG emissions inventory
Relevant Policies/Programs:  RGGI, C40 Cities Climate Leadership Group, ICLEI Local Governments for Sustainability, FLPMA, CAA
Potential Users:  OCO-2 Science Team, Environmental Defense Fund Methane Initiative, CMS Arlyn Andrews
Stakeholders:  Science community (Point of Contact: Various contacts)
Current Application Readiness Level:  3
Start Application Readiness Level:  1
Target Application Readiness Level:  3
Future Developments:  
Limitations:  
Date When Product Available:  2018-05-25
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://daac.ornl.gov/NACP/guides/WRF_STILT_Footprints_Boston.html
Data Server URL(s):

https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1572
Archived Data Citation:  Nehrkorn, T., M. Sargent, S.C. Wofsy, and M. Mountain. 2018. WRF-STILT Gridded Footprints for Boston, MA, USA, 2013-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1572

Bounding Coordinates:
West Longitude:-169.50000 East Longitude:-50.50000
North Latitude:69.50000 South Latitude:10.50000

Product Title:  WRF-STILT Particle Trajectories for Boston, MA, USA, 2013-2014
Start Date:  07/2013      End Date:  12/2014
Description:  This dataset provides Weather Research and Forecasting (WRF) Stochastic Time-Inverted Lagrangian Transport (STILT) particle trajectory data and footprint products for two receptors located in Boston, Massachusetts, USA, for July 2013 - December 2014. Meteorological fields from version 3.6.1 of the Weather Research and Forecasting model are used to drive STILT. STILT applies a Lagrangian particle dispersion model backwards in time from a measurement location (the "receptor" location), to create the adjoint of the transport model in the form of a "footprint" field. The footprint, with units of mixing ratio (ppm) per surface flux (umol m-2 s-1), quantifies the influence of upwind surface fluxes on CO2 and CH4 concentrations measured at the receptor and is computed by counting the number of particles in a surface-influenced volume and the time spent in that volume. Footprints are provided for the two receptors at two temporal and spatial scales: three days of surface influence over the whole North American coverage area at 1-degree resolution and 24 hours of surface influence within a smaller region close to the measurement locations ('near field') at 0.1-degree resolution.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Boston, Massachusetts
Spatial Resolution:  1-degree for foot1 data; 0.1-degree for footnearfield1 data
Temporal Frequency:  Hourly
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  Science community (Point of Contact: Various contacts)
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  May 2018
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1596
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1596
Archived Data Citation:  Nehrkorn, T., M. Sargent, S.C. Wofsy, and M. Mountain. 2018. WRF-STILT Particle Trajectories for Boston, MA, USA, 2013-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1596

Bounding Coordinates:
West Longitude:-81.78000 East Longitude:-65.93000
North Latitude:49.19000 South Latitude:34.51000

Product Title:  CO2 Observations, Modeled Emissions, and NAM-HYSPLIT Footprints, Boston MA, 2013-2014
Start Date:  09/2013      End Date:  12/2014     (Fall 2013 through 2014)
Description:  This dataset reports continuous atmospheric measurements of CO2 from two receptor sites and three boundary sites in and around Boston, Massachusetts, USA, that were combined with high-resolution CO2 emissions estimates and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to estimate regional CO2 emissions from September 2013 to December 2014. The HYSPLIT model followed an ensemble of 1,000 particles released at the urban CO2 measurement sites backward in time based on wind fields and turbulence from the North American Mesoscale Forecast System (NAM) at 12-km resolution to the boundary CO2 measurement sites to derive footprint values and CO2 enhancements expected from the prior emissions based on the Anthropogenic Carbon Emissions System (ACES) inventory and the urban-Vegetation Photosynthesis Respiration Model (urbanVPRM). This dataset contains three sets of data products: (1) observed hourly mean CO2 observations for two urban receptor sites in Boston, MA (Boston University (BU) and Copley Square (COP)), (2) observed hourly mean CO2 and calculated vertical profiles (50 - 5000 m) for three boundary sites around Boston including Harvard Forest at Petersham, MA (HF), Canaan, NH (CA), and Martha's Vineyard, MA (MVY), and modeled mean boundary CO2 concentrations for particles released from BU and COP, and (3) particle trajectory files including footprint values and CO2 enhancements above boundary CO2 concentrations from the HYSPLIT model.
Status:  Archived
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux; MRV
Keywords:  
Spatial Extent:  Massachusetts, Rhode Island, New Hampshire, and area congruent with the ACES emissions inventory, in the Northeastern USA
Spatial Resolution:  Point measurements
Temporal Frequency:  Hourly
Input Data Products:  in-situ and remote CO2 observations along the Boston to Washington DC corridor; Mini MPL measurements at 3 locations in the corridor
Algorithm/Models Used:  
Evaluation:  All measurements undergo continuous QA/QC, calibration against NOAA standards, and intercalibration
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Measurement errors are known based on instrument characteristics; representativity errors estimated using model-data mismatch
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  MRV; GHG emissions inventory
Relevant Policies/Programs:  RGGI, C40 Cities Climate Leadership Group, ICLEI Local Governments for Sustainability, FLPMA, CAA
Potential Users:  OCO-2 Science Team, Environmental Defense Fund Methane Initiative, CMS Arlyn Andrews
Stakeholders:  Environmental Defense Fund (Point of Contact: Steven Hamburg, Shamburg@edf.org; Joe Rudek, jrudek@edf.org); National Institute of Standards and Technology, Greenhouse Gas and Climate Science Measurement (Point of Contact: Dr. James Whetstone, james.whetstone@nist.gov, Anna Karion, anna.karion@nist.gov); National Oceanic and Atmospheric Administration / Earth System Research Laboratory Global Monitoring Divisio (Point of Contact: Dr. Arlyn Andrews, Arlyn.Andrews@noaa.gov); Science community (Point of Contact: Various contacts)
Current Application Readiness Level:  4
Start Application Readiness Level:  1
Target Application Readiness Level:  4
Future Developments:  
Limitations:  
Date When Product Available:  12/31/2016
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1586
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1586
Archived Data Citation:  Sargent, M., S.C. Wofsy, and T. Nehrkorn. 2018. CO2 Observations, Modeled Emissions, and NAM-HYSPLIT Footprints, Boston MA, 2013-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1586

Bounding Coordinates:
West Longitude:-72.18000 East Longitude:-70.00000
North Latitude:43.71000 South Latitude:41.35000

Product Title:  DARTE Annual On-road CO2 Emissions on a 1-km Grid, Conterminous USA, V2, 1980-2017
Start Date:  01/1980      End Date:  12/2017     (1980-2012)
Description:  This data set provides a 38-year, 1-km resolution inventory of annual on-road CO2 emissions for the conterminous United States based on roadway-level vehicle traffic data and state-specific emissions factors for multiple vehicle types on urban and rural roads as compiled in the Database of Road Transportation Emissions (DARTE). CO2 emissions from the on-road transportation sector are provided annually for 1980-2017 as a continuous surface at a spatial resolution of 1 km.
Status:  Archived
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux; MRV
Keywords:  Source, Flux, Evaluation, Uncertainties
Spatial Extent:  CONUS
Spatial Resolution:  1km
Temporal Frequency:  Annual
Input Data Products:  Highway Performance Monitoring System (HPMS) dataset
Algorithm/Models Used:  
Evaluation:  Within the HPMS database, the annual vehicle miles traveled (VMT) information was inspected by county and functional class to identify potential outliers or structural breaks in the dataset. A filtering algorithm flagged any observation in an individual county/functional class time series if the magnitude of the year-on-year difference between an observation and adjacent years was greater than two standard deviations from the mean year-on-year difference of that time series. Of the 761,759 observations in the dataset, roughly 10% were flagged and replaced by the filtering procedure.
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Direct quantification of the uncertainty in US on-road emissions is made impossible by the absence of independent data sources against which to compare government estimates.
Uncertainty Categories:  
Application Areas:  MRV; Urbanization policies; GHG emissions inventory
Relevant Policies/Programs:  Regional Greenhouse Gas Initiative (RGGI), C40 Cities Climate Leadership Group, ICLEI Local Governments for Sustainability, Federal Land Policy and Management Act (FLPMA), Clean Air Act (CAA)
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  6
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  November 2017
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1735
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1735
Archived Data Citation:  Gately, C., L.R. Hutyra, and I.S. Wing. 2019. DARTE Annual On-road CO2 Emissions on a 1-km Grid, Conterminous USA, V2, 1980-2017. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1735

Bounding Coordinates:
West Longitude:-137.26000 East Longitude:-62.04000
North Latitude:53.39000 South Latitude:22.09000

Product Title:  Methane and Ethane Observations for Boston, MA, 2012-2020
Start Date:  08/2012      End Date:  05/2020     (2012-09-01 to 2020-05-30)
Description:  This dataset provides the hourly average of continuous atmospheric measurements of methane (CH4) from two urban sites and three boundary sites in and around Boston, Massachusetts, U.S., from September 2012-May 2020, measured with Picarro cavity ring down spectrometers (CRDS). Five-minute average atmospheric measurements of ethane (C2H6) and methane at Copley Square in Boston, MA, are also provided, with ethane measured with a laser spectrometer and methane measured with a Picarro CRDS. Background CH4 concentrations for the urban sites were determined using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model trajectories at the boundary of the study region based on measurements at three boundary sites and wind direction from the North American Mesoscale Forecast System (NAM) 12-kilometer meteorology.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  NON-METHANE HYDROCARBONS/VOLATILE ORGANIC COMPOUNDS; methane
Spatial Extent:  Massachusetts and New Hampshire, U.S.
Spatial Resolution:  Point measurements
Temporal Frequency:  5-minutes or 1 hour
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1982
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1982
Archived Data Citation:  Sargent, M., S.C. Wofsy, C. Floerchinger, J. Buddy, and E.W. Gottlieb. 2022. Methane and Ethane Observations for Boston, MA, 2012-2020. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1982

Bounding Coordinates:
West Longitude:-72.40000 East Longitude:-69.80000
North Latitude:43.71000 South Latitude:41.50000

 
Publications: Barrera, Y. D., Nehrkorn, T., Hegarty, J., Sargent, M., Benmergui, J., Gottlieb, E., Wofsy, S. C., DeCola, P., Hutyra, L., Jones, T. 2019. Using Lidar Technology To Assess Urban Air Pollution and Improve Estimates of Greenhouse Gas Emissions in Boston. Environmental Science & Technology. 53(15), 8957-8966. DOI: 10.1021/acs.est.9b00650

Barrera, Yanina Débora: Using Lidar Technology and the STILT Model to Assess Air Pollution and Improve Estimates of Greenhouse Gas Emissions in Cities, Ph.D. thesis, July, 2019, 102pp.

Decina, S. M., Templer, P. H., Hutyra, L. R. 2018. Atmospheric Inputs of Nitrogen, Carbon, and Phosphorus across an Urban Area: Unaccounted Fluxes and Canopy Influences. Earth's Future. 6(2), 134-148. DOI: 10.1002/2017EF000653

Floerchinger, Cody: Airborne methane flux quantification and source identification using high resolution measurements of ethane and methane, Ph.D. thesis, Harvard University, July, 2019, 161pp.

Gately, C. K., Hutyra, L. R. 2017. Large Uncertainties in Urban-Scale Carbon Emissions. Journal of Geophysical Research: Atmospheres. 122(20). DOI: 10.1002/2017JD027359

Gately, C. K., Hutyra, L. R., Peterson, S., Sue Wing, I. 2017. Urban emissions hotspots: Quantifying vehicle congestion and air pollution using mobile phone GPS data. Environmental Pollution. 229, 496-504. DOI: 10.1016/j.envpol.2017.05.091

Hardiman, B. S., Wang, J. A., Hutyra, L. R., Gately, C. K., Getson, J. M., Friedl, M. A. 2017. Accounting for urban biogenic fluxes in regional carbon budgets. Science of The Total Environment. 592, 366-372. DOI: 10.1016/j.scitotenv.2017.03.028

Jones, Taylor: Advances in Environmental Measurement Systems: Remote Sensing of Urban Methane Emissions and Tree Sap Flow Quantification, Ph. D. Thesis, Harvard University, Sep. 2019.

Propp, Adrienne M., "MethaneSat: Detecting Methane Emissions from the Barnett Shale Region", Senior Thesis in Applied Mathematic, Harvard Paulson School of Engineering and Applied Science, 2017, 83pp.

Reinmann, A. B., Hutyra, L. R. 2016. Edge effects enhance carbon uptake and its vulnerability to climate change in temperate broadleaf forests. Proceedings of the National Academy of Sciences. 114(1), 107-112. DOI: 10.1073/pnas.1612369114

Sargent, M. R., Floerchinger, C., McKain, K., Budney, J., Gottlieb, E. W., Hutyra, L. R., Rudek, J., Wofsy, S. C. 2021. Majority of US urban natural gas emissions unaccounted for in inventories. Proceedings of the National Academy of Sciences. 118(44). DOI: 10.1073/pnas.2105804118

Sargent, M., Barrera, Y., Nehrkorn, T., Hutyra, L. R., Gately, C. K., Jones, T., McKain, K., Sweeney, C., Hegarty, J., Hardiman, B., Wang, J. A., Wofsy, S. C. 2018. Anthropogenic and biogenic CO 2 fluxes in the Boston urban region. Proceedings of the National Academy of Sciences. 115(29), 7491-7496. DOI: 10.1073/pnas.1803715115

Viatte, C., Lauvaux, T., Hedelius, J. K., Parker, H., Chen, J., Jones, T., Franklin, J. E., Deng, A. J., Gaudet, B., Verhulst, K., Duren, R., Wunch, D., Roehl, C., Dubey, M. K., Wofsy, S., Wennberg, P. O. 2017. Methane emissions from dairies in the Los Angeles Basin. Atmospheric Chemistry and Physics. 17(12), 7509-7528. DOI: 10.5194/acp-17-7509-2017

Archived Data Citations: Gately, C., and L.R. Hutyra. 2018. CMS: CO2 Emissions from Fossil Fuels Combustion, ACES Inventory for Northeastern USA. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1501

Sargent, M., S.C. Wofsy, and T. Nehrkorn. 2018. CO2 Observations, Modeled Emissions, and NAM-HYSPLIT Footprints, Boston MA, 2013-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1586

Nehrkorn, T., M. Sargent, S.C. Wofsy, and M. Mountain. 2018. WRF-STILT Gridded Footprints for Boston, MA, USA, 2013-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1572

Nehrkorn, T., M. Sargent, S.C. Wofsy, and M. Mountain. 2018. WRF-STILT Particle Trajectories for Boston, MA, USA, 2013-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1596

Gately, C., L.R. Hutyra, and I.S. Wing. 2019. DARTE Annual On-road CO2 Emissions on a 1-km Grid, Conterminous USA, V2, 1980-2017. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1735

Sargent, M., S.C. Wofsy, C. Floerchinger, J. Buddy, and E.W. Gottlieb. 2022. Methane and Ethane Observations for Boston, MA, 2012-2020. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1982


 

Olofsson (CMS 2015) (2016)
Project Title:Tracking carbon emissions and removals by time series analysis of the land surface: prototype application in tropical MRV systems compliant with IPCC Tier 3

Science Team
Members:

Pontus Olofsson, NASA MSFC (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2015)
Successor Projects: Woodcock (CMS 2018)  
Abstract: Many tropical countries are experiencing high rates of forest disturbance with of cycles of degradation, cultivation and recovery, but neither the activities nor the terrestrial carbon dynamics associated with the activities are properly tracked in existing REDD+ related Measurement, Reporting and Verification (MRV) systems. This situation is especially true for post-disturbance landscapes and degraded forests, as the trajectories of the land surface activities and carbon dynamics following disturbance are gradual in nature and inherently difficult to monitor. We propose to improve modeling of the carbon dynamics of areas that have experienced disturbance by combining a time series-based approach for monitoring changes on the land surface with a spatially and temporally explicit carbon bookkeeping approach. We have developed algorithms that track the land surface by analyzing time series of all available observations from the Landsat sensors complemented by data from space-borne radar instruments and other optical sensors. Implementations are currently underway across the United States and the Colombian Amazon. Additionally, we have developed open source software tools and educational materials that provide detailed hands-on instructions in support of capacity building efforts in collaboration with SilvaCarbon. We propose a novel framework for estimation of carbon emissions and removals by including detailed information on the fate of the landscape. We will modify a recently developed bookkeeping model so that it runs at the pixel-level (spatially explicit) by directly integrating the results of time series information on conversion between land categories and forest degradation. The characterization of post-disturbance tropical landscapes is critical for accurate accounting of terrestrial carbon pools and fluxes because of the high productivity and carbon density of forests in this region. Therefore, in addition to the time series analysis of the land surface, the temporal dynamics of vegetation structure and recovery following disturbance will be investigated using existing space-borne lidar data in combination with data from upcoming NASA lidar missions. Following best practices protocols for statistical inference of change in area and carbon emissions, unbiased estimates with the uncertainty quantified in the form of confidence intervals will be constructed. Prototype applications of the proposed methodology will be implemented in Colombia and Cambodia, two tropical countries representing different levels of capacity and different types of forest disturbance. A SilvaCarbon effort is underway to complete a comprehensive time series-based analysis of the conversions between the land categories and post-disturbance landscapes across the Colombian Amazon that will be used together with a set of existing field measurements of biomass in a prototype application of the proposed methodology. The methodology will be implemented in Cambodia, where field-measured data on biomass are scarcer, capacity needs greater and the rate of deforestation and forest degradation higher. Engagement with stakeholders and countries will be enhanced by collaboration with in-country SilvaCarbon activities focused on enhancing and supporting systems of MRV for REDD+ activities (including the provision of input for designing field measurement programs). In addition, a spatially and temporally explicit model for estimating the carbon dynamics related to land surface activities will be added to the open source suite of software to provide a more complete framework for the enhancement of MRV systems in the tropics.
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • MRV

Participants:

Gustavo Galindo, IDEAM, Ministry of Environment and Sustainable Development, Colombia Government
Lucy Hutyra, Boston University
Pontus Olofsson, NASA MSFC
Andrew Reinmann, Boston University
Curtis Woodcock, Boston University

Project URL(s): None provided.
 
Data
Products:
Product Title:  Data cube of Landsat data, land cover and land cover conversion of the country of Cambodia
Time Period:  2000-2016
Description:  Data cube constructed using data from Landsats 5,7,8 to which CCDC has been applied for classification and change detection ("activity data"). Surface reflectance predictions for each spectral band allows for generation of synthetic Landsat for any date during the time period
Status:  Planned
CMS Science Theme(s):  Decision Support; MRV
Keywords:  MRV, activity data, REDD, IPCC, data cube, Landsat, land cover, land use, land change
Spatial Extent:  Cambodia
Spatial Resolution:  30 m
Temporal Frequency:  Daily
Input Data Products:  Surface reflectance from Landsat TM/ETM+/OLI; training data
Algorithm/Models Used:  CCDC
Evaluation:  Stratified estimation protocol implemented for construction of unbiased estimators of area and accuracy with confidence interval
Intercomparison Efforts/Gaps:  No
Uncertainty Estimates:  Each mapped category (i .e. each category of activity data) is estimated from sample data including 95% confidence intervals
Uncertainty Categories:  1. Ensemble (design-based inference)
Application Areas:  MRV, deforestation and land use related policies
Relevant Policies/Programs:  UNFCCC, REDD, REDD+
Potential Users:  Governments, NGOs, academia
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  4
Target Application Readiness Level:  9
Future Developments:  Currently being constructed
Limitations:  High processing and storage requirements
Date When Product Available:  Summer 2017
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Spatiotemporal estimates of carbon emissions and removals resulting land change in Cambodia
Time Period:  2000-2016
Description:  Carbon dynamics esimated by applying bookkeeping model to data cube of land conversion
Status:  Planned
CMS Science Theme(s):  Decision Support; MRV
Keywords:  Carbon, emissions factors, MRV, activity data, REDD, IPCC, data cube, Landsat, land cover, land use, land change
Spatial Extent:  Cambodia
Spatial Resolution:  30 m
Temporal Frequency:  Daily
Input Data Products:  Data cube, carbon content variables, growth curves, emssion curves
Algorithm/Models Used:  C-CCDC (carbon bookkeeping model coupled with CCDC)
Evaluation:  None yet
Intercomparison Efforts/Gaps:  No
Uncertainty Estimates:  None yet
Uncertainty Categories:  1. Ensemble (design-based inference) planned
Application Areas:  MRV, deforestation and land use related policies
Relevant Policies/Programs:  UNFCCC, REDD, REDD+
Potential Users:  Governments, NGOs, academia
Stakeholders:  
Current Application Readiness Level:  4
Start Application Readiness Level:  2
Target Application Readiness Level:  9
Future Developments:  Currently being constructed
Limitations:  How to translate population-scale parameters of bias and uncertainty to the pixel level
Date When Product Available:  2018
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Data cube of Landsat data, land cover and land cover conversion of the Colombia Amazon
Time Period:  2000-2016
Description:  Data cube constructed using data from Landsats 5,7,8 to which CCDC has been applied for classification and change detection ("activity data"). Surface reflectance predictions for each spectral band allows for generation of synthetic Landsat for any date during the time period
Status:  Public
CMS Science Theme(s):  Decision Support; MRV
Keywords:  MRV, activity data, REDD, IPCC, data cube, Landsat, land cover, land use, land change
Spatial Extent:  The Colombian Amazon
Spatial Resolution:  30 m
Temporal Frequency:  Daily
Input Data Products:  Surface reflectance from Landsat TM/ETM+/OLI; training data
Algorithm/Models Used:  CCDC
Evaluation:  Stratified estimation protocol implemented for construction of unbiased estimators of area and accuracy with confidence interval
Intercomparison Efforts/Gaps:  No
Uncertainty Estimates:  Each mapped category (i .e. each category of activity data) is estimated from sample data including 95% confidence intervals
Uncertainty Categories:  1. Ensemble (design-based inference)
Application Areas:  MRV, deforestation and land use related policies
Relevant Policies/Programs:  UNFCCC, REDD, REDD+
Potential Users:  Governments, NGOs, academia
Stakeholders:  
Current Application Readiness Level:  8
Start Application Readiness Level:  4
Target Application Readiness Level:  9
Future Developments:  Currently being tested by implementing agency in Colombia
Limitations:  High processing and storage requirements
Date When Product Available:  Spring 2017
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Data cube of pixel-level omission and commission error probabilities of land cover conversion of the Colombia Amazon
Description:  
Status:  Public
CMS Science Theme(s):  
Keywords:  
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  4
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Spatiotemporal estimates of carbon emissions and removals resulting land change in the Colombia Amazon
Time Period:  2000-2016
Description:  Carbon dynamics esimated by applying bookkeeping model to data cube of land conversion
Status:  Public
CMS Science Theme(s):  Decision Support; MRV
Keywords:  Carbon, emissions factors, MRV, activity data, REDD, IPCC, data cube, Landsat, land cover, land use, land change
Spatial Extent:  The Colombian Amazon
Spatial Resolution:  30 m
Temporal Frequency:  Daily
Input Data Products:  Data cube, carbon content variables, growth curves, emssion curves
Algorithm/Models Used:  C-CCDC (carbon bookkeeping model coupled with CCDC)
Evaluation:  None yet
Intercomparison Efforts/Gaps:  No
Uncertainty Estimates:  None yet
Uncertainty Categories:  1. Ensemble (design-based inference) planned
Application Areas:  MRV, deforestation and land use related policies
Relevant Policies/Programs:  UNFCCC, REDD, REDD+
Potential Users:  Governments, NGOs, academia
Stakeholders:  IDEAM, Ministry of Environment and Sustainable Development, Colombia Government (Point of Contact: Gustavo Galindo (gusgalin@gmail.com))
Current Application Readiness Level:  6
Start Application Readiness Level:  2
Target Application Readiness Level:  9
Future Developments:  Currently being constructed
Limitations:  How to translate population-scale parameters of bias and uncertainty to the pixel level
Date When Product Available:  Fall 2017
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  CMS: Landsat-derived Annual Land Cover Maps for the Colombian Amazon, 2001-2016
Start Date:  01/2001      End Date:  12/2016     (2001-2016)
Description:  This dataset provides annual maps of land cover classes for the Colombian Amazon from 2001 through 2016 that were created by classifying time segments detected by the Continuous Change Detection and Classification (CCDC) algorithm. The CCDC algorithm detected changes in Landsat pixel surface reflectance across the time series, and the time segments were classified into land cover types using a Random Forest classifier and manually collected training data. Annual maps of land cover were created for each Landsat scene and then post-processed and mosaicked. Land cover types include unclassified, forest, natural grasslands, urban, pastures, secondary forest, water, or highly reflective surfaces. The training data are not included with this dataset.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  Colombian Amazon
Spatial Resolution:  30 m
Temporal Frequency:  annual
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1783
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1783
Archived Data Citation:  Arévalo, P. 2020. CMS: Landsat-derived Annual Land Cover Maps for the Colombian Amazon, 2001-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1783

Bounding Coordinates:
West Longitude:-78.03000 East Longitude:-65.95000
North Latitude:5.38000 South Latitude:-3.88000

 
Publications: Arevalo, P., Bullock, E. L., Woodcock, C. E., Olofsson, P. 2020. A Suite of Tools for Continuous Land Change Monitoring in Google Earth Engine. Frontiers in Climate. 2. DOI: 10.3389/fclim.2020.576740

Arevalo, P., Olofsson, P., Woodcock, C. E. 2020. Continuous monitoring of land change activities and post-disturbance dynamics from Landsat time series: A test methodology for REDD+ reporting. Remote Sensing of Environment. 238, 111051. DOI: 10.1016/j.rse.2019.01.013

Bullock, E. L., Woodcock, C. E., Souza, C., Olofsson, P. 2020. Satellite-based estimates reveal widespread forest degradation in the Amazon. Global Change Biology. 26(5), 2956-2969. DOI: 10.1111/gcb.15029

Olofsson, P., Arevalo, P., Espejo, A. B., Green, C., Lindquist, E., McRoberts, R. E., Sanz, M. J. 2020. Mitigating the effects of omission errors on area and area change estimates. Remote Sensing of Environment. 236, 111492. DOI: 10.1016/j.rse.2019.111492

Tang, X., Hutyra, L. R., Arevalo, P., Baccini, A., Woodcock, C. E., Olofsson, P. 2020. Spatiotemporal tracking of carbon emissions and uptake using time series analysis of Landsat data: A spatially explicit carbon bookkeeping model. Science of The Total Environment. 720, 137409. DOI: 10.1016/j.scitotenv.2020.137409

Tang, X., Woodcock, C. E., Olofsson, P., Hutyra, L. R. 2021. Spatiotemporal assessment of land use/land cover change and associated carbon emissions and uptake in the Mekong River Basin. Remote Sensing of Environment. 256, 112336. DOI: 10.1016/j.rse.2021.112336

Archived Data Citations: Arévalo, P. 2020. CMS: Landsat-derived Annual Land Cover Maps for the Colombian Amazon, 2001-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1783


 

Saatchi (CMS 2015) (2016)
Project Title:Annual GHG Inventory and MRV System for the US Forestlands

Science Team
Members:

Sassan Saatchi, Jet Propulsion Laboratory / Caltech (Project Lead)
Alexis (Anthony) Bloom, Jet Propulsion Lab, California Institute of Technology
Kevin Bowman, JPL
Yifan Yu, UCLA

Solicitation:NASA: Carbon Monitoring System (2015)
Precursor Projects: Saatchi (CMS 2011)   Masek-Nemani-Saatchi-Tucker (2009)  
Successor Projects: Saatchi (CMS 2020)  
Abstract: We propose to use the CMS infrastructure developed in our earlier pilot project and MRV prototypes to perform an updated annual Green House Gas (GHG) inventory of the US forestlands and contribute to the existing national MRV and the US Forest Service and the Environmental Protection Agency (EPA) national reporting to the United Nation Framework Convention on Climate Change (UNFCCC). The proposed work will produce spatial products on carbon stocks and fluxes that include stakeholder requirements on attributions and uncertainty and deliver at low-latency in order to be integrated in the national carbon management, decision making, and the official national MRV system. With the participation of stakeholders in the process of developing the products, for the first time, NASA CMS program will have the opportunity to directly contribute in the national GHG inventory. The overall objectives of the proposed work are: 1. Develop spatial products on carbon pools and fluxes over the US forestlands including Alaska with the low latency to be used for annual reporting 2. Quantify all sources and sinks and attributions by combining spatial data on forest cover change, pools, and fluxes into the CARDAMOM model data fusion framework 3. Quantify and report uncertainty for all components of sources and sinks in the US forestlands 4. Benchmark the methodology and products for integration in the national MRV system and future stakeholder’s activities. The proposed CMS activity will advance the remote sensing techniques and product by: 1) quantifying changes of forest cover with all natural and anthropogenic attributions at the annual cycle with low-latency delivery, 2) integrating remote sensing and in-situ observations on carbon pools and fluxes in a diagnostic ecosystem carbon balance model to improve carbon sinks and sources for different attributions associated with annual changes in the US forestlands, 3) improve characterization and quantification of errors and uncertainty following the IPCC good practice guidelines, and 4) including stakeholders interests and requirements by directly involving the user community and allowing the evaluation of CMS products for decision making and integration in the national MRV system. By including Alaska, the proposed work will use satellite and airborne and existing in- situ observations to compensate for the lack of extensive forest inventory data and provide, for the first time, the GHG inventory including all pools and fluxes, for both managed and unmanaged forests of the region. The methodology, including the CMS infrastructure for data processing, analysis, uncertainty assessment and data products will be benchmarked to allow integration in national MRV system. The benchmarking will also provide transparency in the entire performance of the carbon monitoring infrastructure for reporting and verification in future carbon trading protocols.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • MRV

Participants:

Alexis (Anthony) Bloom, Jet Propulsion Lab, California Institute of Technology
Kevin Bowman, JPL
Grant Domke, USDA Forest Service
Stephen (Steve) Hagen, Applied Geosolutions
Taejin Park, NASA Ames Research Center / BAERI
Sassan Saatchi, Jet Propulsion Laboratory / Caltech
Christopher (Chris) Woodall, USDA Forest Service
Yifan Yu, UCLA

Project URL(s): None provided.
 
Data
Products:
Product Title:  Carbon Pools across CONUS using the MaxEnt Model, 2005, 2010, 2015, 2016, and 2017
Start Date:  01/2005      End Date:  12/2017     (2005, 2010, 2015, 2016, 2017)
Description:  This dataset provides annual estimates of six carbon pools, including forest aboveground live biomass, belowground biomass, aboveground dead biomass, belowground dead biomass, litter, and soil organic matter, across the conterminous United States (CONUS) for 2005, 2010, 2015, 2016, and 2017. Carbon stocks were estimated using a modified MaxEnt model. Measurements of pixel-specific site conditions from remote sensing data were combined with field inventory data from the U.S. Forest Service Forest Inventory and Analysis (FIA). Remote sensing data inputs included Thematic Mapper on Landsat 5, Operational Land Imager on Landsat 8, Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua, microwave radar measurements from Phased Array type L-band Synthetic Aperture Radar (PALSAR) on Advanced Land Observation Satellite (ALOS) and PALSAR-2 ALOS-2, airborne imagery from National Agriculture Imagery Program (NAIP), and the digital elevation model from the Shuttle Radar Topography Mission (SRTM). Data from satellite and airborne sources were co-registered on a common 100 m (1 ha) grid.
Status:  Archived
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux
Keywords:  terrestrial carbon pools, forest
Spatial Extent:  CONUS
Spatial Resolution:  1 ha
Temporal Frequency:  Annual mean for select years
Input Data Products:  Landsat5, Landsat8, SRTM, ALOS, ALOS2, FIA Inventory
Algorithm/Models Used:  Modified Maximum Entropy, CARDAMOM
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1752
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1752
Archived Data Citation:  Yu, Y., S.S. Saatchi, B.F. Walters, S. Ganguly, S. Li, S. Hagen, L. Melendy, R.R. Nemani, G.M. Domke, and C.W. Woodall. 2021. Carbon Pools across CONUS using the MaxEnt Model, 2005, 2010, 2015, 2016, and 2017. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1752

Bounding Coordinates:
West Longitude:-130.23000 East Longitude:-64.13000
North Latitude:52.86000 South Latitude:21.59000

 
Publications: Hogan, J. A., Domke, G. M., Zhu, K., Johnson, D. J., Lichstein, J. W. 2024. Climate change determines the sign of productivity trends in US forests. Proceedings of the National Academy of Sciences. 121(4). DOI: 10.1073/pnas.2311132121

Yu, Y., Saatchi, S., Domke, G. M., Walters, B., Woodall, C., Ganguly, S., Li, S., Kalia, S., Park, T., Nemani, R., Hagen, S. C., Melendy, L. 2022. Making the US national forest inventory spatially contiguous and temporally consistent. Environmental Research Letters. 17(6), 065002. DOI: 10.1088/1748-9326/ac6b47

Archived Data Citations: Yu, Y., S.S. Saatchi, B.F. Walters, S. Ganguly, S. Li, S. Hagen, L. Melendy, R.R. Nemani, G.M. Domke, and C.W. Woodall. 2021. Carbon Pools across CONUS using the MaxEnt Model, 2005, 2010, 2015, 2016, and 2017. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1752