融合光学与雷达遥感数据的城市不透水面提取方法

Fusing Optical and SAR Remote Sensing Data for Urban Impervious Surface Estimation

该文概述了利用多源遥感技术提取城市不透水面的研究进展,分析通过融合光学和合成孔径雷达(SAR)遥感数据提高不透水面提取精度的必要性和技术难点。以香港岛为实验区,选择了3种不同波段(L、C和X波段)、不同空间分辨率和不同极化方式(HH、HV和VV)的SAR卫星数据,分别与光学卫星SPOT-5数据进行特征级融合,并对城市不透水面提取的效果进行分析。实验结果表明,融合光学和SAR数据可以提高不透水面的提取精度,一定程度上降低了暗不透水面和裸土的混淆现象。其次,使用双极化SAR比单极化SAR数据具有更高的提取精度,而提高SAR数据的空间分辨率则没有达到提高精度的效果。

This paper presents an overview of the research progress in impervious surface estimation using multi-source remote sensing technology,with a focus on the technical significance and challenges of fusing optical and synthetic aperture radar （SAR） remote sensing data for impervious surface estimation.Taking the Hong Kong Island as an example,the study selected SAR data sets of various wavelengths,i.e.L-,C- and X-bands,and various polarizations,i.e.HH,HV and VV,to be fused with optical data of SPOT-5.The fusion was designed at the feature level to investigate its effectiveness for impervious surface estimation.Experiments indicated that fusing optical and SAR data is able to improve the accuracy by reducing the confusion between dark impervious surface and bare soil;and the contribution from multiple polarizations is better than that from high spatial resolution regarding the improvement of accuracy.