Remote Sensing-Based Land Use and Land Cover Change in Shalamulun Catchment

In this study, the decision tree (DT) classification technique was used to detect the land use changes based on the spectral characteristics of the samples and the spatial patterns of the six land use classes for two landsat images for the Shalamulun river catchment of China acquired in 1987 and 2001. And post-classification change detection technique was applied to map land cover changes. For validating the classification results, detailed field data of the land cover as well as land use was recorded with the help of a mobile mapping system equipped with GPS. Changes among different land cover classes were assessed based on the information extraction technique, spatial analysis technique and mathematical statistics method, supported by GIS software. During the study period, the land cover changes were distinctly on grassland and forest. In this study, we analyzed the quantity change, spatial-temporal change and the extent of land use change in the catchment by spatial analysis and revealed the driving forces of land use and land cover change.