Land cover and land use classification based on remote sensing intelligent Geo interpreting model
遥感地学智能图解模型支持下的土地覆盖／土地利用分类

Land cover/land use has become one of the crucial but basic tasks in carrying out a series of important work,such as the prediction of land use change,prevention of natural disasters,management and planning of land use,protection of environment,etc.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.In this article,after we firstly present the RSIGIM model,the intelligent land cover/land use classification framework and system is built up.Based on remote sensing intelligent Geo interpretation model (RSIGIM),the characteristics of traditional RS classification models can be synthetically integrated so that the Geo decision knowledge can be structurally and parametrically fused into.The target aims to build a new systematic structure of land cover/land use classification with the experimental case in Hong Kong,with the support of the data fusion model between the multi platform remotely sensed data and ancillary geographic data.