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摘要： 基于面向对象和区域增长的方法，开展东营市城乡建设用地提取。通过分析局部斑点统计特征计算真实的纹理影像，并对强度数据进行多尺度分割，结合纹理影像信息和局部后向散射强度信息，应用面向对象和区域生长方法提取城乡建设用地。利用Google Earth提供的影像进行对照验证，生成混淆矩阵来评价城乡建设用地提取结果。在东营市的高分辨率TerraSAR\|X数据的实验结果验证了本方法的有效性，提取精度达92.89%。 关键词： TerraSAR-X;  城乡建设用地;  影像分割;  面向对象;  区域生长     Abstract: Urban sprawl stands for one of the most dynamic process in the context of global land use changes.Currently developing countries are going through the tide of urban expansion，represented by China and India.The constantly increasing loss of land resources due to growing settlements comes along with various ecological and socioeconomic challenges such as air pollutant，water contamination，urban heat island effect and urban waterlog disaster.In order to prevent these negative consequences，effective methods and strategies for a sustainable development of urban planning is the availability of accurate and up\|to\|date geo\|data on the location，shape，and dynamics of built\|up areas.Based on single\|polarized TerraSAR\|X，the approach generates homogeneous segments on an arbitrary number of scale levels by applying a region\|growing algorithm，which takes the intensity of backscatter and shape\|related properties into account.The object\|oriented procedure consists of three main steps:firstly，the analysis of the local speckle behavior in the SAR intensity data，leading to the generation of a texture image；secondly，a segmentation based on the intensity image；thirdly，the classification of each segment using the derived texture file and intensity information in order to identify and extract build\|up areas.In our research，the distribution of BAs in Dongying City is derived from single\|polarized TSX SM image (acquired on 17th June 2013)with average ground resolution of 3m using our proposed approach.By cross\|validating the random selected validation points with geo\|referenced field sites，Google Earth high\|resolution imagery，confusion matrices with statistical indicators are calculated and used for assessing the classification results.The result of kappa coefficient is 0.85，OA coefficient is 92.89%.We have shown that connect texture information with the analysis of the local speckle divergence，combining texture and intensity of construction extraction is feasible，efficient and rapid.

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