基于Sentinel-2A和Landsat8的城市不透水面的提取

Impervious surface extraction based on Sentinel-2A and Landsat8

城市不透水面相关研究对城市的发展至关重要。为了提取城市不透水面盖度,通常采用线性光谱混合分析方法,在亚像元尺度上计算混合像元内的不透水面面积比例。由于端元光谱曲线存在误差,导致不透水面盖度提取精度较低,因而提出端元优化方案,通过Sentinel-2A影像选择比较纯净的端元,利用其光谱信息优化从Landsat8影像中选择的端元的光谱曲线,提高纯净像元光谱曲线精度。此外,结合解混结果优化方案,利用归一化植被指数(normalized differential vegetation index,NDVI)和干旱裸土指数(dry bare-soil index,DBSI),对解混结果进行优化。采用WorldView-2遥感影像进行样本验证,结果显示,该方法所提取不透水面盖度的精度比传统方法提高了20%,为端元选取和不透水面提取提供可靠的理论支持。

The extraction of impervious surface(IS)is very important for the development of cities,and linear spectral mixture analysis is commonly adopted to calculate the fraction of IS in the mixed pixel to improve the extraction of the urban IS at the subpixel scale.Owing to errors in the spectra of pure pixels selected from remote sensing images,incorrect fractions of different land cover types often emerge after unmixing.In this paper,the modified endmember selection was proposed to improve the accuracy of the spectral information of endmembers.Sentinel-2A images were applied to selected endmembers to get the spectral,which was used to modify the spectral information of the endmembers from Landsat8.In addition,the optimization scheme of LSMA results in which the normalized differential vegetation index(NDVI)and dry bare-soil index(DBSI)thresholds are used to optimize the mixing results was applied to improve the accuracy of LSMA results.With the WorldView-2 remote sensing image for sample verification,the results showed that the accuracy of IS fraction extracted by the method in this paper was 20%higher than that of the traditional method,providing reliable theoretical support for endmember selection and IS extraction.