A method of land use/land cover change detection from remote sensing image based on support vector machines

Land cover/land use has become one of the crucial but basic tasks in carrying out a series of important work. With the development of remote sensing techniques and Geo analysis model, using remotely sensed data to monitor the status and dynamical change of land cover/land use has become one of the most rapid, credible and effectual approaches. To improve the accuracy of change detection from remote sensing image, this paper introduces a new method of change detection from remote sensing image based on support vector machine (SVM), using multi-spectral remote sensing data. We choose Hengshui city in China as a typical studying sample. The result shows that it is competitive with other recently developed methods for change detection when applied to the same data sets and yield good performance with very limited training data.