Object-oriented Classification Approach for Remote Sensing Imagery Information Extraction in Loess Hilly-gully Region
The object-oriented classification approach was employed in loess hilly-gully region. Taking typical watershed Yan'gou as example, ALOS satellite images were used. The object-oriented multi-segmentation was carried out with multi-spectral, panchromatic imagery, auxiliary data of digital evaluation model (DEM) and the normalized difference vegetation index (NDVI). The land-use categories closely related to ecosystem restoration, fanning and living, such as forest, grass, farmland, orchard, settlement and water, were classified with thresholds. The classification results had promising accuracies, and the overall classification accuracy was 77.73% .
国家科技期刊平台
NSTL
万方数据
维普
