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NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms

  • the SBG Algorithms Working Group
  • Jet Propulsion Laboratory, California Institute of Technology
  • University of Wisconsin-Madison
  • King Abdulaziz City for Science and Technology
  • Boeing
  • Istituto Nazionale Di Geofisica E Vulcanologia
  • University of Maryland, Baltimore County
  • NASA Goddard Space Flight Center
  • United States Geological Survey
  • Instituto Tecnológico Vale
  • Michigan State University
  • University of Arizona
  • University of Utah
  • University of Connecticut
  • Universities Space Research Association
  • University of California at San Diego
  • NASA Ames Research Center
  • Oklahoma State University
  • University of New South Wales
  • Boise State University
  • HySpeed Computing
  • Northern Arizona University
  • Bermuda Institute of Ocean Sciences
  • University of South Florida
  • University of California at Santa Cruz
  • Arizona State University
  • Naval Research Laboratory
  • Kent State University
  • Science Systems and Applications, Inc.
  • University of California Los Angeles
  • University of Nebraska-Lincoln
  • University of California at Santa Barbara
  • University of Zurich
  • Brookhaven National Laboratory

Research output: Contribution to journalReview articlepeer-review

298 Scopus citations

Abstract

The 2017–2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a “Designated Targeted Observable” (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380–2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3–5 μm; TIR: 8–12 μm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algorithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. This effort synthesizes the findings of more than 130 scientists.

Original languageEnglish
Article number112349
JournalRemote Sensing of Environment
Volume257
DOIs
StatePublished - May 2021

Keywords

  • Aquatic
  • Hyperspectral
  • Remote sensing
  • Snow
  • Thermal infrared
  • Vegetation
  • Volcano

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