Abstract
Desertification is severely threatening the agricultural production and social stability in the 21st century. Traditionally,
desertification assessment is indicated by Vegetation Coverage (VC), which can be derived from remote sensing data.
However, vegetation indices are inefficient when VC is less than 15%. A simplified desertification monitoring approach
based on Kauth-Thomas Tasseled Cap Transformation (K-TTCT) is proposed in this paper: First, brightness, greenness
and wetness information was produced using landsat5 TM images by K-TTCT. The non density model was used for the
reversion of VC. And the brightness, greenness, wetness and VC were plotted in n-visualization. They plotted nearly in a
linear shape when the data was rotated to a certain view angle. Then their characteristics in n-D visualization were
analyzed and training samples were selected with the help of n-D visualizer. Finally, a case study was carried out in
Guyuan county, Heibei province, China using the approach proposed in this paper. It shows that this approach can
overcome the deficiency of traditional desertification assessment approaches and produce a better desertification
assessment outputs with an overall accuracy higher than 85%.
