Hierarchical object oriented land cover classification method using SPOT 5 imagery in waste dump opencast coalmine area

Land cover classification with a high accuracy in waste dump area is very important to ecoenvironment research, vegetation condition study and soil recovery destination. Funded by the international cooperation project Novel Indicator Technologies for Minesite Rehabilitation and sustainable development, a hierarchical object oriented land cover classification is produced in this study. There are two steps: image segmentation and classification. First, the image is segmented using chessboard segmentation and multiresolution segmentation method. Second, NDVI is used to distinguish vegetation and non-vegetation. Accuracy assessment indicate that this hierarchical method can be used to do land cover classification in waste dump area, the total accuracy increases to 86.53%, and Kappa coefficient increases to 0.7907.

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