气候变化领域集成服务门户(CCPortal): Quantifying uncertainty for remote spectroscopy of surface composition

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DOI	10.1016/j.rse.2020.111898
	Quantifying uncertainty for remote spectroscopy of surface composition
	Thompson D.R.; Braverman A.; Brodrick P.G.; Candela A.; Carmon N.; Clark R.N.; Connelly D.; Green R.O.; Kokaly R.F.; Li L.; Mahowald N.; Miller R.L.; Okin G.S.; Painter T.H.; Swayze G.A.; Turmon M.; Susilouto J.; Wettergreen D.S.
发表日期	2020
ISSN	00344257
卷号	247
英文摘要	Remote surface measurements by imaging spectrometers play an important role in planetary and Earth science. To make these measurements, investigators calibrate instrument data to absolute units, invert physical models to estimate atmospheric effects, and then determine surface properties from the spectral reflectance. This study quantifies the uncertainty in this process. Global missions demand predictive uncertainty models that can estimate future errors for varied environments and observing conditions. Here we validate uncertainty predictions with remote surface composition retrievals and in situ measurements in a field analogue of Earth and planetary exploration. We consider rover transects at Cuprite, Nevada, and remote observations by NASA's Next-Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). We show that accounting for input uncertainties can benefit mineral detection methods such as constrained spectrum fitting. This suggests that operational uncertainty estimates could improve future NASA missions like the Earth Mineral dust source InvesTigation (EMIT) and the Lunar Trailblazer mission, as well as NASA's Decadal Surface Biology and Geology (SBG) Investigation. © 2020 Elsevier Inc.
英文关键词	Atmospheric correction; Calibration visible-shortwave infrared; Cuprite Nevada; Geologic mapping; Hyperspectral imagers; Imaging spectroscopy; Statistical methods
语种	英语
scopus关键词	Infrared spectrometers; Interplanetary spacecraft; Lunar missions; NASA; Surface measurement; Thermography (imaging); Airborne visible infrared imaging spectrometer; Atmospheric effects; Imaging spectrometers; In-situ measurement; Planetary exploration; Predictive uncertainty; Spectral reflectances; Uncertainty estimates; Uncertainty analysis; AVIRIS; detection method; Earth; NSCAT; uncertainty analysis; Cuprite; Nevada; 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/179262
作者单位	Jet Propulsion Laboratory, California Institute of Technology, United States; Carnegie Mellon University, Pittsburgh, PA 15213, United States; Cornell University, Ithaca, NY, United States; University of California Los Angeles, Los Angeles, CA, United States; NASA Goddard Institute for Space Studies and Columbia University, New York, NY, United States; Planetary Science Institute, Lakewood, CO, United States; U. S. Geological Survey (USGS), Denver, CO, United States
推荐引用方式 GB/T 7714	Thompson D.R.,Braverman A.,Brodrick P.G.,et al. Quantifying uncertainty for remote spectroscopy of surface composition[J],2020,247.
APA	Thompson D.R..,Braverman A..,Brodrick P.G..,Candela A..,Carmon N..,...&Wettergreen D.S..(2020).Quantifying uncertainty for remote spectroscopy of surface composition.Remote Sensing of Environment,247.
MLA	Thompson D.R.,et al."Quantifying uncertainty for remote spectroscopy of surface composition".Remote Sensing of Environment 247(2020).