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Separating snow and forest temperatures with thermal infrared remote sensing

TitleSeparating snow and forest temperatures with thermal infrared remote sensing
Publication TypeJournal Article
Year of Publication2018
AuthorsLundquist J.D, Chickadel C., Cristea N., Currier W.R, Henn B., Keenan E., Dozier J.
JournalRemote Sensing of Environment
Date Published2018/05
Type of ArticleArticle
ISBN Number0034-4257
Accession NumberWOS:000430897300053
Keywordsair; cover; covered area; emissivity; Environmental Sciences & Ecology; Forest temperature; Fractional snow; Imaging Science &; in-situ; incoming longwave radiation; Land Surface Temperature; land-surface temperature; m atmospheric; melting snow; Mixed pixel; modis; Photographic Technology; Remote sensing; Snow surface temperature; Thermal infrared; trunk temperatures; window

Thermal infrared sensing from space is a well-developed field, but mixed pixels pose a problem for many applications. We present a field study in Dana Meadows, Yosemite National Park, California to scale from point (similar to 2-m resolution) to aerial (similar to 5-m resolution gridded, 1 km x 6 km extent) to satellite (MODIS, similar to 1000-m resolution, global extent) observations. We demonstrate how multiple thermal bands on MODIS can be used to separate snow and forest temperatures and determine the fractional snow-covered area (f(scA)) over a 3 km x 3 km array of 9 MODIS grid cells. During the day, visible, near-infrared, and shortwave-infrared bands provide a first guess of f(scA) and help to constrain the solution. This technique, which has estimated errors < 2 degrees C and 10% f(scA) for many expected conditions, enables better understanding of the snowpack energy balance, atmospheric inversions and cold air pools, and forest health.

Short TitleRemote Sens. Environ.
Student Publication: