Red Willow Coleman , David R. Thompson , Philip G. Brodrick , Eyal Ben Dor , Evan Cox , Carlos Pérez García-Pando , Todd Hoefen , Raymond F. Kokaly , John M. Meyer , Francisco Ochoa , Gregory S. Okin , Daniela Heller Pearlshtien , Gregg Swayze , Robert O. Green
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引用次数: 0
Abstract
The Earth surface Mineral dust source InvesTigation (EMIT) is an imaging spectrometer launched to the International Space Station in July 2022 to measure the mineral composition of Earth’s dust-producing regions. We present a systematic accuracy assessment of the EMIT surface reflectance product in two parts. First, we characterize the surface reflectance product’s overall performance using multiple independent vicarious calibration field experiments with hand-held and automated field spectrometers. We find that the EMIT surface reflectance product has a standard error of % in absolute reflectance units for temporally coincident observations. Discrepancies rise to % for spectra acquired at different dates and times of day, which we attribute mainly to changes in solar geometry. Second, we develop an error budget that explains the differences between EMIT and in-situ field spectrometer data. We find that uncertainties in spatial footprints, field spectroscopy, and the EMIT-reported measurement were sufficient to explain discrepancies in most cases. Our approach did not detect any systematic calibration or reflectance errors in the timespan considered. Together, these findings demonstrate that a space-based imaging spectrometer can acquire high-quality spectra across a wide range of observational and atmospheric conditions.
期刊介绍:
Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing.
The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques.
RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.