The extraction of water information based on SPOT5 image using object-oriented method

The paper realizes water body extraction well using object-oriented classification method based on SPOT5 image. Firstly, segment image according to multi-scale image segmentation method based on edge-detection algorithm. Secondly, determine various characteristic parameters in land surface features according to object characteristics such as spectrum, shape and texture. And thirdly, use SVM (Support Vector Machine) method to achieve object classification through the establishment of the sample rules, and extract water body successfully. It takes SPOT5 image in Xiaojiaqiao section of Chaping River in Anxian County, Mianyang City, Sichuan Province, China as a case study. The results show that, compared with pixel-oriented supervised classification method, object-oriented classification method applied in water information extraction is more effective and its classification accuracy is higher.