28 January 2002 Directional satellite thermal IR measurements and modeling of a forest in winter and their relationship to air temperature
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Data assimilation methods applied to hydrologic models can incorporate spatially distributed maps of near surface temperature, especially if such measurements can be reliably inferred from satellite observations. Uncalibrated thermal IR imagery sometimes is scaled to temperature units to obtain such observations using the assumption that dense forest canopies are close to air temperature. For fully leafed deciduous forest canopies in the summer, this approximation is usually valid within 2C. In a leafless canopy, however, the materials views are thick boles and branches and the forest floor, which can store heat and yield significantly higher variations. Winter coniferous forests are intermediate with needles and branches being the predominant viewed materials. The US Dept of Energy's Multispectral Thermal Imager (MTI) is an experimental satellite with the capability to perform quantitative scene measurements in the reflective and thermal infrared region respectively. Its multispectral thermal IR capability enables quantitative surface temperature retrieval if pixel emissivity is known. MTI is pointable and targets multiple times in the winter and spring of 2001 at the Howland, Maine AmeriFlux research site operated by the University of Maine. Supporting meteorological and optical depth measurements also were made from three towers at the site. Directional thermal models of forest woody materials and needles are driver by the surface measurements and compared to satellite data to help evaluate the relationship between air temperature and satellite thermal measurements as a function of look angles, day and night.
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Lee K. Balick, Lee K. Balick, Jerrell R. Ballard, Jerrell R. Ballard, James Alan Smith, James Alan Smith, Stewart M. Goltz, Stewart M. Goltz, } "Directional satellite thermal IR measurements and modeling of a forest in winter and their relationship to air temperature", Proc. SPIE 4542, Remote Sensing for Agriculture, Ecosystems, and Hydrology III, (28 January 2002); doi: 10.1117/12.454212; https://doi.org/10.1117/12.454212


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