B039-01
Modeling to Support End-to-End Traceability of Reflectance to Algorithms for the Surface Biology and Geology Designated Observable (MEET-SBG)

Wednesday, 9 December 2020: 05:30
Virtual
Benjamin Poulter1, Kerry-Anne Cawse-Nicholson2, Michelle Gierach3, Glynn C Hulley2, David Schimel4, Shawn Serbin5, Alexey N Shiklomanov6, David R Thompson4, Philip A Townsend7, Weile Wang8, Anh Nguyen9 and Shannon Kian Zareh10, (1)NASA GSFC, Biospheric Science, Greenbelt, MD, United States, (2)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (3)NASA Jet Propulsion Laboratory, Oceans and Ice Group, Pasadena, CA, United States, (4)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (5)Brookhaven National Laboratory, Environmental and Climate Sciences Department, Upton, NY, United States, (6)NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD, United States, (7)University of Wisconsin, Department of Forest and Wildlife Ecology, Madison, WI, United States, (8)CSUMB & NASA/AMES, Seaside, CA, United States, (9)NASA ARC, Mountain View, United States, (10)Jet Propulsion Laboratory, Pasadena, CA, United States
Abstract:
Remote sensing relies on a complex workflow to derive surface reflectance and higher-level products from at-sensor radiances. At each stage of this workflow, various sources of uncertainty emerge that are related to instrument noise, sun-sensor geometry, atmospheric conditions, the inversion or retrieval algorithm, and the product algorithm itself. Quantifying the sources of uncertainty within a simulation framework can help support mission design and optimize architectural configurations to reduce risk and to provide robust products to the science and applications community. An End-to-End Traceability simulator is currently in development for the NASA Surface Biology and Geology (SBG) Designated Observable to contribute in the assessment of measurement objectives and potential instrument configurations. “Modeling End-to-End Traceability in support of SBG”, or MEET-SBG, consists of four components that include local to global uncertainty quantification, cover hyperspectral visible to shortwave infrared (VSWIR) wavelengths and multispectral thermal infrared (TIR) emissions, and considers a multi-dimensional space of viewing conditions for a variety of research focal areas. Here we will present examples for each component, discuss their synergies for combining VSWIR and TIR, and how MEET-SBG contributes to the design and evaluation of the SBG architecture study.
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