中文摘要：

高精度地获取县（或县级市）域土地利用/覆被的定性、定量信息对于维护生态环境和保障我国农村经济的可持续发展具有重要意义。针对2003年冬季所获得的江苏省新沂市的TM图像特点,选择分层信息提取法提取土地利用/覆被信息。首先对图像进行基于最大似然法的监督分类,观察分类结果,提取误分、错分比例最小的未利用地类型,然后采用光谱分析法提取出水体范围、监督分类和目视解译相结合法提取出城镇建设用地和农村居民点、归一化植被指数提取出林地,最后提取出耕地。信息提取结果与同期土地利用图相比较,整个新沂市域范围内土地利用/覆被类型分类的面积精度达到96.17%,空间精度达到88.38%,表明这种方法提取遥感图像土地利用/覆被信息是可行的。

英文摘要：

It is important to achieve the qualitative and quantitative information of land use/cover in a county（or county-level city）of China with higher precision,which is helpful to enhance eco-environment protection and sustainable development of rural economy.Presently,remote sensing images of the medium and high resolution are mostly used to monitor the changes of land use/cover in a county.To make better use of remote sensing technology in monitoring land use change,it is necessary to improve the automatization level of information extraction from the remote sensing images and meet the precision of change monitoring synchronically.Hierarchical information extraction is an effective method for information extraction of land use/cover in a county from the remote sensing images.Based on the information of each ground object,the image is decomposed layer upon layer according to certain principles.The method functions well in the classification precision over ＂the same object with different spectra＂ and ＂different objects with the same spectrum＂ because the environment of information extraction is comparatively pure.Aided by the TM image in Xinyi city of Jiangsu province obtained in the winter of 2003,the hierarchical method is used to extract the information of land use/cover.On the basis of such processes of original images as geometric correction,image registration,image clip and image enhancement,first of all,the image was classified using the maximum likelihood classifier and the unused land with the least inaccurate probability was extracted from the classification result observed.Then,the scope of the water was extracted using spectral analysis method,the urban construction land and village by combining supervised classification method with visual interpretation method,and the woodland using Normalized Difference Vegetation Index（NDVI）.Finally,the cropland was extracted.By comparing extracted result of land use/cover with the land use map in the same period,the area accuracy of the land use classifi