以西安市为研究区,以Landsat8 OLI/TIRS遥感影像为数据源,先采用支持向量机(SVM)提取城市不透水面信息;再以单窗算法反演城市地表温度;然后对不透水面与地表温度之间的关系进行随机样点回归分析。结果表明,不透水面与地表温度之间存在显著的相关性,空间格局具有高度一致性,即不透水面增加的区域地表温度也随之升高,反之亦然。因此,随着不透水面的快速增加,若要形成生态、绿色、健康、可持续的城市生态环境,应同时对城市绿化进行合理的规划和布局。

Taking Xi'an City as the study area, based on Landsat8 OLI/TIRS images, we used support vector machine(SVM) method to extract the urban impervious surface information at first. And then, we inverted the urban surface temperature by mono-window algorithm. Finally, we carried out a random sampling regression analysis between the urban impervious surface and surface temperature. The results show that there is a significant correlation between the urban impervious surface and surface temperature, and the spatial pattern is highly consistent, namely when the impervious surface increased then the local surface temperature will increase, and vice versa. With a rapid increase of urban impervious surface, in order to form an ecological, green, healthy and sustainable urban ecological environment, we should carry out reasonable planning and layout of urban greening at the same time.