Project Funding: 2016 - 2019

NRA: 2015 NASA: Carbon Monitoring System   

Funded by NASA

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+.

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

More details may be found in the following project profile(s):

• NASA Terrestrial Ecology (TE) Project Profile
• North American Carbon Program (NACP) Project Profile
• NASA Carbon Monitoring System (CMS) Project Profile