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Multidimensional Disaggregation of Land Surface Temperature Using High-Resolution Red, Near-Infrared, Shortwave-Infrared, and Microwave-L Bands

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5 Author(s)
Merlin, O. ; Centre d''Etudes Spatiales de la Biosphere (CESBIO), Toulouse, France ; Jacob, F. ; Wigneron, J.-P. ; Walker, J.
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Land surface temperature data are rarely available at high temporal and spatial resolutions at the same locations. To fill this gap, the low spatial resolution data can be disaggregated at high temporal frequency using empirical relationships between remotely sensed temperature and fractional green (photosynthetically active) and senescent vegetation covers. In this paper, a new disaggregation methodology is developed by physically linking remotely sensed surface temperature to fractional green and senescent vegetation covers using a radiative transfer equation. Moreover, the methodology is implemented with two additional factors related to the energy budget of irrigated areas, being the fraction of open water and soil evaporative efficiency (ratio of actual to potential soil evaporation). The approach is tested over a 5 km by 32 km irrigated agricultural area in Australia using airborne Polarimetric L-band Multibeam Radiometer brightness temperature and spaceborne Advanced Scanning Thermal Emission and Reflection radiometer (ASTER) multispectral data. Fractional green vegetation cover, fractional senescent vegetation cover, fractional open water, and soil evaporative efficiency are derived from red, near-infrared, shortwave-infrared, and microwave-L band data. Low-resolution land surface temperature is simulated by aggregating ASTER land surface temperature to 1-km resolution, and the disaggregated temperature is verified against the high-resolution ASTER temperature data initially used in the aggregation process. The error in disaggregated temperature is successively reduced from 1.65°C to 1.16°C by including each of the four parameters. The correlation coefficient and slope between the disaggregated and ASTER temperatures are improved from 0.79 to 0.89 and from 0.63 to 0.88, respectively. Moreover, the radiative transfer equation allows quantification of the impact on disaggregation of the temperature at high resolution for each parameter: fracti- nal green vegetation cover is responsible for 42% of the variability in disaggregated temperature, fractional senescent vegetation cover for 11%, fractional open water for 20%, and soil evaporative efficiency for 27%.

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Geoscience and Remote Sensing, IEEE Transactions on  (Volume:50 ,  Issue: 5 )