Application of remote sensing and GIS for anthropogenic vegetation monitoring

Comparison between actual and potential natural vegetation classifications has been done to identify impact of human activities on vegetation distribution over Asian region. The twelve monthly Normalized Difference Vegetation Index (NDVI) derived from NOAA/AVHRR data (1985-1997), together with climatic data, i.e, air temperature, and precipitation were processed by isoclass unsupervised and maximum likelihood algorithm to get the homogeneous spectral classes for land cover categorizing. Through classification trials, 68 clusters were found as the number of vegetation classes over this region. Moreover, the climatic characteristic value of each class, such as temperature, radiation cloudiness, precipitation, and elevation were extracted from available global dataset to determine the potential natural vegetation. By comparing those classifications, we realized, that India (Southern Asia), and some parts of China (Eastern Asia) were the center of land cover changing. This also appears in croplands of Kazakhstan, Indonesia, Mongolia, Thailand, Russia, Pakistan, Nepal, Myanmar (Burma), and Bangladesh.