Annual land use change survey is very important for keeping the land use data of China up-to-date. Currently, Land use change information acquisition is mainly based on artificial visual interpretation, which is low in efficiency. A new method of land use change detection based on multi-source data is presented in this paper. Classification samples for current phase image are acquired form previous phase land use vector data through a processing of sample refining. So automatic classification for current phase image can be implemented, which makes automatic change detected by comparing classification result with previous phase land use. The multivariate alteration detection (MAD) transformation method for the two phase image is used to eliminate pseudo change. The changed polygon objects with accuracy boundary are extracted based on change detect. Experiment shows that the proposed method is more effective with working time less than half that of the traditional method, and can better find real land use change without omission.
赵展, 夏旺, 闫利. 基于多源数据的土地利用变化检测[J]. 国土资源遥感, 2018, 30(4): 148-155.
Zhan ZHAO, Wang XIA, Li YAN. Land use change detection based on multi-source data. Remote Sensing for Land & Resources, 2018, 30(4): 148-155.
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