Abstract
A model of desertification in semi-arid environment employing satellite multi-spectral images is presented. The variables proposed to characterize desertification are: texture of terrain, vegetation index for semi-arid terrain, and albedo of terrain. The texture is derived from a divergence operator applied upon the vector field formed by the first three principal components of the image. The vegetation index selected is the TSAVI, suitable for semi-arid environment where vegetation is scarce. The albedo is calculated from the first principal component obtained from the bands of the multi-spectral image. These three variables are input into a clustering algorithm resulting in six desertification grades. These grades are ordered from no-desertification to severe desertification. Details are provided for the computer calculation of the desertification variables, and the parameters employed in the clustering algorithm. A multi-spectral Landsat TM image is selected for this research. A thematic map of desertification is then generated with the support of ancillary data related to the study area.
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Lira, J. (2004). A Model of Desertification Process in a Semi-arid Environment Employing Multi-spectral Images. In: Sanfeliu, A., Martínez Trinidad, J.F., Carrasco Ochoa, J.A. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2004. Lecture Notes in Computer Science, vol 3287. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30463-0_31
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DOI: https://doi.org/10.1007/978-3-540-30463-0_31
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