A Spectral Angle Distance-Weighting Reconstruction Method for Filled Pixels of the MODIS Land Surface Temperature Product

• Published in: IEEE geoscience and remote sensing letters Vol. 11; no. 9; pp. 1514 - 1518
• Main Authors: Shuai, Tong, Zhang, Xia, Wang, Shudong, Zhang, Lifu, Shang, Kun, Chen, Xiaoping, Wang, Jinnian
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.09.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Filled pixels; Image reconstruction; Land surface; Land surface temperature; land surface temperature (LST); Meteorology; moderate-resolution imaging spectroradiometer (MODIS); MODIS; reconstruction; Remote sensing; spectral angle distance (SAD); Surface reconstruction; Temperature sensors; Filled pixels; reconstruction; moderate-resolution imaging spectroradiometer (MODIS); spectral angle distance (SAD); land surface temperature (LST)
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2013.2297735

Land surface temperature (LST) is an important parameter in the physics of land surface processes, but a large number of pixels are often filled as zero due to cloud, heavy aerosols, and so on in the Moderate-resolution Imaging Spectroradiometer (MODIS) LST product. This letter presents the spectral angle distance (SAD)-weighting reconstruction (SADWER) method of reconstruction of zero-filled pixels of the MODIS LST product. It relies on the hypothesis that pixels with the same land-cover type have nearly the same LST in a localized area. SAD can measure the similarity of land-cover types of different pixels, and pixels with higher land-cover similarity can contribute more to the reconstruction using the weighting method. The result shows that the reconstruction ratio could be as high as 95% using only the SADWER method and nearly 100% after spatial filter postprocessing. The reconstruction accuracy is validated using artificially generated 20-, 50-, and 80-km-diameter concentrically filled areas in both forest and crop land-cover types. The statistical result shows that the standard deviations of the reconstruction errors are less than 2 Kelvin.