城市不透水表面遥感估算研究  

Estimating urban impervious surface distribution with RS

作　　者：袁超[1,2] 吴炳方[2] 罗兴顺[3] 李志伟[1] 闫娜娜[2] 

机构地区：[1]中南大学信息物理工程学院,湖南长沙410083 [2]中科院遥感应用研究所,北京100101 [3]吉林大学应用技术学院,吉林长春130022

出　　处：《测绘工程》2009年第3期32-36,39,共6页Engineering of Surveying and Mapping

基　　金：中国科学院知识创新工程重大项目(KZCX1-YW-08-03);国家科技支撑计划:城镇化与村镇建设动态监控关键技术(2006BAJ11B04-3)

摘　　要：作为城市化水平的关键指示因子,不透水表面已经被广泛应用在城市生态环境评估中。利用TM影像,采用附有限制条件的线性光谱混合模型对北京城区的不透水表面分布进行空间分析。通过高反照率、低反照率、植被及土壤4类光谱端元的线性组合表征城市土地覆盖类型,综合剔除噪声影响后的高、低反照率分量,估算北京城区不透水表面分布。研究结果表明:利用附有限制条件的线性光谱分解得到的RMS平均值为0.003 428。其不透水表面分布结果与同期spot-5对比验证,R2为0.932,均方根误差为0.086,结果令人满意。As a key indicator of urbanization, the impervious surface has been widely used as a urban environmental indicator to estimate urban impervious surface distribution; we can reveal the further change of urban land cover/land use and urban expansion in Beijing. Four endmembers, low albedo, high albedo, vegetation, and soil were implemented through the constrained linear spectral mixture analysis（LSMA） using Landsat Thematic Mapper. In this paper,impervious surface fraction was estimated by analyzing low and high albedo endmembers. The results of this study reveal that estimative impervious surface distribution can be derived with a promising accuracy, the root mean square （RMS） error was 8. 6% and correlation coefficient R2was 0. 932, by comparing to the corresponding true impervious surface digitized through interpreting spot-5 images and the area of imperviousness measured from the digitized map.

关 键 词：不透水表面 线性光谱混合分析 端元 遥感 

分 类 号：P237[天文地球—摄影测量与遥感]