气候变化领域集成服务门户(CCPortal): Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California

CCPortal

DOI	10.1016/j.rse.2020.111779
	Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California
	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.
发表日期	2020
ISSN	00344257
卷号	242
英文摘要	Estimates of the magnitude and distribution of aboveground carbon in Earth's forests remain uncertain, yet knowledge of forest carbon content at a global scale is critical for forest management in support of climate mitigation. In light of this knowledge gap, several upcoming spaceborne missions aim to map forest aboveground biomass, and many new biomass products are expected from these datasets. As these new missions host different technologies, each with relative strengths and weaknesses for biomass retrieval, as well as different spatial resolutions, consistently comparing or combining biomass estimates from these new datasets will be challenging. This paper presents a demonstration of an inter-comparison of biomass estimates from simulations of three NASA missions (GEDI, ICESat-2 and NISAR) over Sonoma county in California, USA. We use a high resolution, locally calibrated airborne lidar map as our reference dataset, and emphasize the importance of considering uncertainties in both reference maps and spaceborne estimates when conducting biomass product validation. GEDI and ICESat-2 were simulated from airborne lidar point clouds, while UAVSAR's L-band backscatter was used as a proxy for NISAR. To estimate biomass for the lidar missions we used GEDI's footprint-level biomass algorithms, and also adapted these for application to ICESat-2. For UAVSAR, we developed a locally trained biomass model, calibrated against the ALS reference map. Each mission simulation was evaluated in comparison to the local reference map at its native product resolution (25 m, 100 m transect, and 1 ha) yielding RMSEs of 57%, 75%, and 89% for GEDI, NISAR, and ICESat-2 respectively. RMSE values increased for GEDI's power beam during simulated daytime conditions (64%), coverage beam during nighttime conditions (72%), and coverage beam daytime conditions (87%). We also test the application of GEDI's biomass modeling framework for estimation of biomass from ICESat-2, and find that ICESat-2 yields reasonable biomass estimates, particularly in relatively short, open canopies. Results suggest that while all three missions will produce datasets useful for biomass mapping, tall, dense canopies such as those found in Sonoma County present the greatest challenges for all three missions, while steep slopes also prove challenging for single-date SAR-based biomass retrievals. Our methods provide guidance for the inter-comparison and validation of spaceborne biomass estimates through the use of airborne lidar reference maps, and could be repeated with on-orbit estimates in any area with high quality field plot and ALS data. These methods allow for regional interpretations and filtering of multi-mission biomass estimates toward improved wall-to-wall biomass maps through data fusion. © 2020 The Author(s)
英文关键词	Biomass errors; Biomass estimation; Data fusion; GEDI; ICESat-2; NISAR
语种	英语
scopus关键词	Carbon; Data fusion; Earth (planet); Forestry; NASA; Optical radar; Orbits; Uncertainty analysis; Above ground biomass; Above-ground carbons; Biomass estimation; Climate mitigations; Environmental gradient; GEDI; ICESat-2; NISAR; Biomass; aboveground biomass; backscatter; biomass; data assimilation; forest ecosystem; forest management; ICESat; lidar; satellite altimetry; spacecraft; uncertainty analysis; California; Sonoma County; United States
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179341
作者单位	Department of Geographical Sciences, University of Maryland, College Park, United States; Biospheric Sciences Lab, NASA Goddard Space Flight Center, United States; Applied Research Laboratories, University of Texas at Austin, United States; School of GeoSciences, University of Edinburgh, Ireland; Earth System Science Interdisciplinary Center, University of Maryland, College Park, United States; Radar Science and Engineering Section, NASA Jet Propulsion Laboratory, United States; Geodesy and Geophysics Lab, NASA Goddard Space Flight Center, United States; Department of Ecology and Evolutionary Biology, Brown University, United States; Institute at Brown for Environment and Society, Brown University, United States
推荐引用方式 GB/T 7714	Duncanson L.,Neuenschwander A.,Hancock S.,et al. Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California[J],2020,242.
APA	Duncanson L..,Neuenschwander A..,Hancock S..,Thomas N..,Fatoyinbo T..,...&Dubayah R..(2020).Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California.Remote Sensing of Environment,242.
MLA	Duncanson L.,et al."Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California".Remote Sensing of Environment 242(2020).