Analysis of Rocky Desertification Monitoring Using MODIS Data in Western Guangxi, China - Advances in Data, Methods, Models and Their Applications in Geoscience - page 307

4.2 Supervised classification and change analysis
MODIS L1B images in 2000 and 2010 were classified by supervised classification, in which
the maximum likelihood classifying algorithm was employed as the most typical and wide
method. After the ground training and selection of training samples, the image classification
of the MODIS data was performed under ENVI environment. Afterwards, the post-
processing classification was also made to reduce or eliminate the effect of noise caused by
mixed scattered point features. Therefore, a filter kernel 3×3 matrix was used to make
cluster analysis, which can smooth the classification maps and combine the similar areas to
the neighbor region. The final results of the classification maps in 2000, 2003, 2006, 2008 and
2010 were shown in Fig. 5.
Fig. 5. (continued)