北京城市不透水层覆盖度遥感估算

URBAN IMPERVIOUS SURFACE ABUNDANCE ESTIMATION IN BEIJING BASED ON REMOTE SENSING

应用线性光谱混合模型研究城市环境生物物理组成,端元的确定是其关键。城市地表同物异谱现象显著,光谱变异强烈,对于高反照率地物尤其突出。端元的光谱变异对线性光谱混合模型拟合结果产生重要影响。以同种纯净地物光谱曲线形状具有相似性为出发点,提出了一种端元优化选取方法,在此基础上计算了北京城市地表不透水层覆盖度。研究结果表明,该方法能够在一定程度上减小端元光谱变异性对线性光谱混合模型拟合结果的影响,进而提高城市不透水层覆盖度的估算精度。

The linear spectral mixture model （LSMM） is usually used to study the urban environmental biophysical composition. The development of high - quality fraction images depends greatly on the selection of suitable end - members, which constitutes a key step. Spectral variability is obvious in the heterogeneous urban area, especially for high albedo objects, and this phenomenon affects the accuracy of LSMM. The study in this paper is based on the key assumption that the same pure land cover types exhibit obvious spectral similarity. The objective of this study is to examine the applicability of optimizing end - members selection based on spectral similarity. Four end - members, namely, vegetation, soil, low albedo and high albedo, were selected to model urban land cover by using Landsat Thematic Mapper data. Impervious surface abundance was estimated by adding low albedo fraction and caused by end - member spectral variability. The results of this study reveal that impervious surface abundance distribution can be derived with a promising accuracy.