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A unified approach to estimate land and water reflectances with uncertainties for coastal imaging spectroscopy

Thompson, David R. and Cawse-Nicholson, Kerry and Erickson, Zachary and Fichot, Cédric G. and Frankenberg, Christian and Gao, Bo-Cai and Gierach, Michelle M. and Green, Robert O. and Jensen, Daniel and Natraj, Vijay and Thompson, Andrew (2019) A unified approach to estimate land and water reflectances with uncertainties for coastal imaging spectroscopy. Remote Sensing of Environment, 231 . Art. No. 111198. ISSN 0034-4257. doi:10.1016/j.rse.2019.05.017.

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Coastal ecosystem studies using remote visible/infrared spectroscopy typically invert an atmospheric model to estimate the water-leaving reflectance signal. This inversion is challenging due to the confounding effects of turbid backscatter, atmospheric aerosols, and sun glint. Simultaneous estimation of the surface and atmosphere can resolve the ambiguity enabling spectral reflectance maps with rigorous uncertainty quantification. We demonstrate a simultaneous retrieval method that adapts the Optimal Estimation (OE) formalism of Rodgers (2000) to the coastal domain. We compare two surface representations: a parametric bio-optical model based on Inherent Optical Properties (IOPs); and an expressive statistical model that estimates reflectance in every instrument channel. The latter is suited to both land and water reflectance, enabling a unified analysis of terrestrial and aquatic domains. We test these models with both vector and scalar Radiative Transfer Models (RTMs). We report field experiments by two airborne instruments: NASA's Portable Remote Imaging SpectroMeter (PRISM) in an overflight of Santa Monica, California; and NASA's Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG) in an overflight of the Wax Lake Delta and lower Atchafalaya River, Louisiana. In both cases, in situ validation measurements match remote water-leaving reflectance estimates to high accuracy. Posterior error predictions demonstrate a closed account of uncertainty in these coastal observations.

Item Type:Article
Related URLs:
URLURL TypeDescription
Thompson, David R.0000-0003-1100-7550
Erickson, Zachary0000-0002-9936-9881
Frankenberg, Christian0000-0002-0546-5857
Gierach, Michelle M.0000-0002-8161-4121
Natraj, Vijay0000-0003-3154-9429
Thompson, Andrew0000-0003-0322-4811
Additional Information:© 2019 Elsevier Inc. Received 3 July 2018, Revised 1 April 2019, Accepted 14 May 2019, Available online 25 June 2019. Code used in this study is available through the open source ISOFIT project (Thompson and Olson-Duvall, 2018). We thank the PRISM team including: Principal Investigator Pantazis Mouroulis; Mark Helmlinger for calibration; Justin Haag for calibration, instrumentation and deployment; Byron Van Gorp for design and development; Frank Loya; and Scott Nolte for operations. The PRISM flight was enabled by a PRISM AITT grant from NASA ESTO. This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration and funded under the Presidents' and Directors' Fund Program. We thank other supporting sponsors including the NASA Earth Science Division for the AVIRIS-NG instrument and the data analysis program “Utilization of Airborne Visible/Infrared Imaging Spectrometer Next Generation Data from an Airborne Campaign in India” NNH16ZDA001N-AVRSNG, managed by Woody Turner, for its support of the algorithm development; the Jet Propulsion Laboratory Research and Technology Development Program; and the NASA Center Innovation Fund managed in conjunction with the Jet Propulsion Laboratory Office of the Chief Scientist and Technologist. Copyright 2018 California Institute of Technology. All Rights Reserved. US Government Support Acknowledged.
Funding AgencyGrant Number
JPL President and Director's FundUNSPECIFIED
Subject Keywords:Imaging spectroscopy; Coastal and inland waters; Optimal estimation; PRISM; Atmospheric correction; Bio-optical models; Statistical methods; Portable remote imaging SpectroMeter; Hyperspectral imaging
Record Number:CaltechAUTHORS:20190625-110829430
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Official Citation:David R. Thompson, Kerry Cawse-Nicholson, Zachary Erickson, Cédric G. Fichot, Christian Frankenberg, Bo-Cai Gao, Michelle M. Gierach, Robert O. Green, Daniel Jensen, Vijay Natraj, Andrew Thompson, A unified approach to estimate land and water reflectances with uncertainties for coastal imaging spectroscopy, Remote Sensing of Environment, Volume 231, 2019, 111198, ISSN 0034-4257, (
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:96695
Deposited By: Tony Diaz
Deposited On:25 Jun 2019 18:13
Last Modified:16 Nov 2021 17:23

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