Marine Science Faculty Publications
Document Type
Article
Publication Date
2021
Keywords
Hyperspectral, Remote sensing, Thermal infrared, Vegetation, Snow, Volcano, Aquatic
Digital Object Identifier (DOI)
https://doi.org/10.1016/j.rse.2021.112349
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.
Rights Information
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Remote Sensing of Environment, v. 257, art. 112349
Scholar Commons Citation
Cawse-Nicholson, Kerry; Townsend, Philip A.; Schimel, David; Assiri, Ali M.; Blake, Pamela L.; Buongiorno, Maria Fabrizia; Campbell, Petya; Carmon, Nimrod; Casey, Kimberly A.; Correa-Pabón, Rosa Elvira; Dahlin, Kyla M.; Dashti, Hamid; Dennison, Philip E.; Dierssen, Heidi; Erickson, Adam; Fisher, Joshua B.; Frouin, Robert; Gatebe, Charles K.; Gholizadeh, Hamed; Gierach, Michelle; Glenn, Nancy F.; Goodman, James A.; Griffith, Daniel M.; Guild, Liane; Hakkenberg, Christopher R.; Hochberg, Eric J.; Holmes, Thomas R.H.; Hu, Chuanmin; Hulley, Glynn; Huemmrich, Karl F.; Kudela, Raphael M.; Kokaly, Raymond F.; Lee, Christine M.; Martin, Roberta; Miller, Charles E.; Moses, Wesley J.; Muller-Karger, Frank E.; Ortiz, Joseph D.; Otis, Daniel B.; Pahlevan, Nima; Painter, Thomas H.; Pavlick, Ryan; Poulter, Ben; Qi, Yi; Realmuto, Vincent J.; Roberts, Dar; Schaepman, Michael E.; Schneider, Fabian D.; Schwandner, Florian M.; Serbin, Shawn P.; Shiklomanov, Alexey N.; Stavros, E. Natasha; Thompson, David R.; Torres-Perez, Juan L.; Turpie, Kevin R.; Tzortziou, Maria; Ustin, Susan; Yu, Qian; Yusup, Yusri; and Zhang, Qingyuan, "NASA's Surface Biology and Geology Designated Observable: A Perspective on Surface Imaging Algorithms" (2021). Marine Science Faculty Publications. 2200.
https://digitalcommons.usf.edu/msc_facpub/2200