摘要
城市不透水面信息的提取对城市发展至关重要。光谱指数法因形式简单且易于计算,是目前提取不透水面信息的主要方法之一。但由于不透水面与裸土的光谱特征十分相似,光谱指数法提取不透水面时易将裸土误提。针对这一问题,在充分分析裸土与不透水面间的光谱特征差异后,基于Landsat-8 OLI影像的第1、第2、第5和第6波段分别构建了抑制裸土的归一化不透水面指数(bareness-restrained normalized impervious surface index, BRNISI)和抑制裸土的比值不透水面指数(bareness-restrained Ratio impervious surface index, BRRISI)。为评价BRRISI和BRNISI对不透水面的提取性能,选取具有不同地表覆盖的北京市和贵阳市作为研究区进行实验对比。结果表明:BRRISI和BRNISI两种指数较好地解决了不透水面与裸土极易混淆的问题,均能较好地抑制裸土的影响,在北京市的总体精度达94.89%、94.96%,在贵阳市的总体精度达90.25%、90.36%,相较于现有的几种常用不透水面指数,精度都得到了显著提高。
The extraction of urban impervious surface information is crucial for urban development. The spectral exponential method is one of the main methods for extracting information on impervious surfaces due to its simple form and easy calculation. However, due to the fact that the spectral characteristics of the impervious surface and the bare soil are very similar, the spectral exponential index method is easy to mistakenly lift the bare soil when extracting the impervious surface. In view of this problem, after fully analyzing the differences in spectral characteristics between bare soil and impervious surfaces, the bareness-restrained normalized impervious surface index was constructed based on the 1st, 2nd, 5th and 6th bands of Landsat-8 OLI images, respectively, after fully analyzing the differences in spectral features between bare soil and impervious surface. BRRISI for bareness-restrained normalized impervious surface index and ratio impervious surface index (BRRISI) for bareness-restrained. In order to evaluate the extraction performance of BRNISI and BRRISI on impervious surfaces, Beijing and Guiyang cities with different surface covers were selected as study areas for experimental comparison. The results show that the two indexes of BRNISI and BRRISI better solve the problem that the impervious surface and bare soil are easily confused, and both can better inhibit the influence of bare soil, and the overall accuracy in Beijing is 94.89% and 94.96%, and the overall accuracy in Guiyang City is 90.25% and 90.36%, which is sig-nificantly improved compared with the existing several commonly used impervious surface index-es.
出处
《应用数学进展》
2022年第12期8442-8452,共11页
Advances in Applied Mathematics