为了克服利用统一分类模型难以有效提高土地利用分类精度的问题,为土地利用/覆被定性、定量信息的提取提供一种高精度、高效率的提取方法,将分层信息提取法和基于知识规则的信息提取方法相结合,基于对南京市都市区的土地利用时空特点和研究区TM影像数据中各地类波谱信息的分析,结合了地类提取指数模型、DEM数据、城市建成区边界等,充分利用地学先验知识,设计了一套土地信息分层提取的流程,对土地利用信息进行了提取。利用该方法对2012年南京市都市区的土地利用/土地覆被信息提取的总体精度达到了88.67%,Kappa系数达到了0.85。实践证明,基于知识与规则的土地利用信息分层提取方法提取精度较高,适用性强,对其他地区的土地利用/覆被信息分类提取也有一定的借鉴意义。
The purpose of this paper is to overcome the problem that the uniform classification model cannot be used to improve the accuracy of land use classification effectively,and to provide a method with high precision and efficiency to extract qualitative and quantitative information of land use/cover.In this paper,two extraction methods,i.e.,the hierarchical information extraction method and the method based on knowledge and rule,are combined.The hierarchical information extraction method can create a cleaner extracting environment when extracting specific types of land use/cover.The method based on knowledge and rule can give full play to the role of priori knowledge and experience,and reference diverse assistant information comprehensively.The purpose of combining the two methods is to further improve the classification accuracy.Taking the metropolitan area of Nanjing as an example,a set of land use information hierarchical extraction process is designed and put into effect.In the extraction process,TM image spectrum information and the temporal and spatial characteristics of land use in study area are fully considered.Using different ways and data such as water extraction index model,Ratio Resident-area Index(RRI),NDVI,DEM data and the urban built-up area boundary,we extracted eight types of land use/cover,i.e.,water,urban build-up area,rural build-up area,mining land,bare land,woodland,farmland,and urban green land.Specially,we constructed a build-up and quarry discrimination index(BQDI)to efficiently distinguish build-up area from mining/bare land,and make full use of elevation and slope information to extract woodland from vegetation coverage area.In addition,the urban build-up area boundary plays an important role in distinguishing urban build-up area and rural build-up area,farmland and urban green land,mining land and bare land.The results showed that the overall accuracy(OA)reached 88.67%,and the Kappa index reached 0.85 when extracting the land use/cover information of 2012 in study area.Beside