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Full-Text Articles in Engineering
Sharpening Ecostress And Viirs Land Surface Temperature Using Harmonized Landsat-Sentinel Surface Reflectances, Jie Xue, Martha C. Anderson, Feng Gao, Christopher Hain, Liang Sun, Yun Yang, Kyle R. Knipper, William P. Kustas, Alfonso F. Torres-Rua, Mitch Schull
Sharpening Ecostress And Viirs Land Surface Temperature Using Harmonized Landsat-Sentinel Surface Reflectances, Jie Xue, Martha C. Anderson, Feng Gao, Christopher Hain, Liang Sun, Yun Yang, Kyle R. Knipper, William P. Kustas, Alfonso F. Torres-Rua, Mitch Schull
Civil and Environmental Engineering Faculty Publications
Land surface temperature (LST) is a key diagnostic indicator of agricultural water use and crop stress. LST data retrieved from thermal infrared (TIR) band imagery, however, tend to have a coarser spatial resolution (e.g., 100 m for Landsat 8) than surface reflectance (SR) data collected from shortwave bands on the same instrument (e.g., 30 m for Landsat). Spatial sharpening of LST data using the higher resolution multi-band SR data provides an important path for improved agricultural monitoring at sub-field scales. A previously developed Data Mining Sharpener (DMS) approach has shown great potential in the sharpening of Landsat LST using Landsat …