Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping

REMOTE SENSING OF ENVIRONMENT

卷:253

Article

Silva, Carlos Alberto^1,2  Duncanson, Laura¹  Hancock, Steven⁴  Neuenschwander, Amy⁵  Thomas, Nathan^3,6  Hofton, Michelle¹  Fatoyinbo, Lola³  Simard, Marc⁷  Marshak, Charles Z.⁷  Armston, John¹  Lutchke, Scott³  Dubayah, Ralph¹ 

[1] Univ Maryland, Dept Geog Sci, College Pk, MD 20740 USA

[2] Univ Florida, Sch Forest Resources & Conservat, Gainesville, FL 32611 USA

[3] NASA, Biosci Lab, Goddard Space Flight Ctr, Laurel, MD 20707 USA

[4] Univ Edinburgh, Sch GeoSci, Edinburgh, Midlothian, Scotland

[5] Univ Texas Austin, Appl Res Labs, Austin, TX 78712 USA

[6] Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20740 USA

[7] CALTECH, Jet Prop Lab, NASA, 4800 Oak Grove Dr, Pasadena, CA 91109 USA

关键词: Biomass;    Lidar;    Mapping;    Fusion;    Temperate forest;    L-band SAR;   

DOI  :  10.1016/j.rse.2020.112234

来源: Elsevier

【 摘 要 】

Accurate mapping of forest aboveground biomass (AGB) is critical for better understanding the role of forests in the global carbon cycle. NASA's current GEDI and ICESat-2 missions as well as the upcoming NISAR mission will collect synergistic data with different coverage and sensitivity to AGB. In this study, we present a multi-sensor data fusion approach leveraging the strength of each mission to produce wall-to-wall AGB maps that are more accurate and spatially comprehensive than what is achievable with any one sensor alone. Specifically, we calibrate a regional L-band radar AGB model using the sparse, simulated spaceborne lidar AGB estimates. We assess our data fusion framework using simulations of GEDI, ICESat-2 and NISAR data from airborne laser scanning (ALS) and UAVSAR data acquired over the temperate high AGB forest and complex terrain in Sonoma County, California, USA. For ICESat-2 and GEDI missions, we simulate two years of data coverage and AGB at footprint level are estimated using realistic AGB models. We compare the performance of our fusion framework when different combinations of the sparse simulated GEDI and ICEsat-2 AGB estimates are used to calibrate our regional L-band AGB models. In addition, we test our framework at Sonoma using (a) 1-ha square grid cells and (b) similarly sized irregularly shaped objects. We demonstrate that the estimated mean AGB across Sonoma is more accurately estimated using our fusion framework than using GEDI or ICESat-2 mission data alone, either with a regular grid or with irregular segments as mapping units. This research highlights methodological opportunities for fusing new and upcoming active remote sensing data streams toward improved AGB mapping through data fusion.

【 授权许可】

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