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

Autor(es): CAWSE-NICHOLSON, Kerry; TOWNSEND, Philip A.; SCHIMEL, David; ASSIRI, Ali M.; BLAKE, Pamela L.; PABÓN, Rosa Elvira Correa et al.
Resumo: (EN) 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.
Periódico: Remote Sensing of Environment
Ano: 2021
Volume: v. 257
DOI: https://doi.org/10.1016/j.rse.2021.112349
Ano de publicação: 2021
Disponível em: https://www.sciencedirect.com/science/article/pii/S0034425721000675?via%3Dihub
Editora com ISSN: Elsevier