基于热红外遥感数据和光谱混合分解模型的城市不透水面估算

doi:10.11849/zrzyxb.2012.09.016

自然资源学报 ›› 2012, Vol. 27 ›› Issue (9): 1590-1600.doi: 10.11849/zrzyxb.2012.09.016

基于热红外遥感数据和光谱混合分解模型的城市不透水面估算

李波^1,2, 黄敬峰^2,3, 吴次芳¹

1. 浙江大学东南土地管理学院, 杭州 310058;
2. 浙江省农业遥感与信息技术重点实验室, 杭州 310058;
3. 浙江大学农业遥感与信息技术应用研究所, 杭州310058

收稿日期:2011-12-20 修回日期:2012-04-25 出版日期:2012-09-20 发布日期:2012-09-20
基金资助:
国家自然科学基金资助项目(40871158,51108405)。

Estimating Urban Impervious Surface Based on Thermal Infrared Remote Sensing Data and a Spectral Mixture Analysis Model

LI Bo^1,2, HUANG Jing-feng^2,3, WU Ci-fang¹

1. Institute of Southeast Land Management, Zhejiang University, Hangzhou 310058, China;
2. Key Laboratory of Agricultural Remote Sensing and Information System in Zhejiang Province, Hangzhou 310058, China;
3. Institute of Agricultural Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310058, China

Received:2011-12-20 Revised:2012-04-25 Online:2012-09-20 Published:2012-09-20

摘要/Abstract

摘要： 不透水面的迅速增长是城市化的显著特征之一,针对大范围的城市监测,运用遥感技术迅速提取城市不透水面是当前国内外研究的热点。论文选用Landsat 7的ETM+影像,基于光谱混合分解模型,结合热红外遥感数据反演生成的地表温度,研究杭州市的不透水面分布信息的提取。通过高、低反照率、植被及土壤4类光谱端元的线性组合来表征不同城市土地类型,并利用地表温度和土壤分量分别剔除高、低反照率分量中的"噪声",综合修正后的高反照率分量和低反照率分量估算杭州市不透水面分布。结果显示,研究区中均方根误差的平均值为0.003 6,不透水面分布结果与同期Google earth上的高分辨率影像和SPOT 4影像的解译结果对比分析,绝大多数样本的估算值与解译值之差落在±0.15区间内,精度令人满意。研究表明,热红外遥感数据和光谱混合分解模型相结合,可以实现对不透水面进行快速、精确的估算。

关键词: 遥感, 不透水面, 光谱混合分解, 热红外数据

Abstract: The rapid growth of impervious surface is one of the remarkable characteristics of urbanization. Rapid extraction of urban impervious surface using remote sensing has been a hotspot research at home and abroad for large-scale urban monitoring. This paper explored extraction of impervious surface information of Hangzhou from a Landsat 7 ETM+ image based on the integration of a spectral mixture analysis model and land surface temperature generated by thermal infrared images. The linear combination of high albedo, low albedo, vegetation and soil fraction was used to characterize the different types of urban land. The land surface temperature was considered as a mask to remove the "noise" from low albedo fraction, and soil fraction was used to remove the "noise" from high albedo fraction. The modified high albedo fraction and low albedo fraction were adopted to estimate impervious surface distribution of Hangzhou. The result showed that the average RMSE was 0.0036 in the study area. Impervious surface distribution estimated using the above method and the interpretation from high resolution images in Google earth and SPOT 4 image was comparatively analyzed, and the majority of differences between estimating values and interpreting values of samples were ranged from -0.15 to +0.15. There was a promising accuracy. The result indicated that the method was feasible and reliable to precisely estimate impervious surface based on thermal infrared remote sensing images and a spectral mixture analysis model.

Key words: remote sensing, impervious surface, spectral mixture analysis, thermal infrared data

中图分类号:

TP79

李波, 黄敬峰, 吴次芳. 基于热红外遥感数据和光谱混合分解模型的城市不透水面估算[J]. 自然资源学报, 2012, 27(9): 1590-1600.

LI Bo, HUANG Jing-feng, WU Ci-fang. Estimating Urban Impervious Surface Based on Thermal Infrared Remote Sensing Data and a Spectral Mixture Analysis Model[J]. JOURNAL OF NATURAL RESOURCES, 2012, 27(9): 1590-1600.

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基于热红外遥感数据和光谱混合分解模型的城市不透水面估算

Estimating Urban Impervious Surface Based on Thermal Infrared Remote Sensing Data and a Spectral Mixture Analysis Model

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