气候变化领域集成服务门户(CCPortal): Generalized radiative transfer emulation for imaging spectroscopy reflectance retrievals

CCPortal

DOI	10.1016/j.rse.2021.112476
	Generalized radiative transfer emulation for imaging spectroscopy reflectance retrievals
	Brodrick P.G.; Thompson D.R.; Fahlen J.E.; Eastwood M.L.; Sarture C.M.; Lundeen S.R.; Olson-Duvall W.; Carmon N.; Green R.O.
发表日期	2021
ISSN	00344257
卷号	261
英文摘要	Estimates of surface reflectance from observed radiance are fundamentally tied to the accuracy of the radiative transfer models used to simulate the interaction of light with the atmosphere and surface. These radiative transfer models are parameterized by a wide range of quantities, ranging from observation and solar geometries to assumptions about atmospheric conditions, including vertical distributions aerosols and water vapor as well as the atmospheric composition. However, current retrieval approaches cannot represent this variability; they are limited by computational expense to a coarsely-spaced look up table (LUT) of just a few parameters. Here, we propose a new method called sRTMnet that facilitates the efficient creation of dense LUT grids that fully capture radiative transfer's inherent nonlinearity. sRTMnet uses a combination of fast, reduced-order radiative transfer modeling coupled with neural-network-based emulation to realize a computational speedup of over 3000× while maintaining the accuracy of a high-fidelity RTM. We demonstrate the accuracy of sRTMnet in multiple ways. We show that neural-network-based emulation delivers accurate atmospheric properties using robust testing sets. We then use acquisitions from the airborne visible/infrared imaging spectrometer - next generation (AVIRIS-NG) to show near identical surface reflectance estimates with sRTMnet and a high-fidelity radiative transfer model (MODTRAN). Finally, we show how distributions of mapped minerals remain consistent when using the sRTMnet-based reflectance. Given these results, sRTMnet will be utilized for the upcoming Earth Surface Mineral Dust Source Investigation (EMIT, an imaging spectrometer destined for the international space station in 2022). In addition to speed and accuracy, the fully open-source nature of sRTMnet (including simulation and emulation), provides a pathway for high-resolution imaging spectroscopy reflectance retrievals at the global scale. © 2021 The Authors
英文关键词	AVIRIS; Earth surface mineral dust source investigation (EMIT); Hyperspectral; RTM
语种	英语
scopus关键词	Hyperspectral imaging; Minerals; Radiative transfer; Reflection; Space stations; Spectrometers; Table lookup; Earth surface mineral dust source investigation (EMIT); High-fidelity; HyperSpectral; Imaging spectroscopy; Look-up-table; Network-based; Neural-networks; Parameterized; Radiative transfer modelling; Surface reflectance; Dust
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/178813
作者单位	Jet Propulsion Laboratory, California Institute of Technology, United States
推荐引用方式 GB/T 7714	Brodrick P.G.,Thompson D.R.,Fahlen J.E.,et al. Generalized radiative transfer emulation for imaging spectroscopy reflectance retrievals[J],2021,261.
APA	Brodrick P.G..,Thompson D.R..,Fahlen J.E..,Eastwood M.L..,Sarture C.M..,...&Green R.O..(2021).Generalized radiative transfer emulation for imaging spectroscopy reflectance retrievals.Remote Sensing of Environment,261.
MLA	Brodrick P.G.,et al."Generalized radiative transfer emulation for imaging spectroscopy reflectance retrievals".Remote Sensing of Environment 261(2021).