2015年尼泊尔地震以其强大的破坏力诱发了许多滑坡,对居民生命安全、道路房屋等造成极大的威胁,更准确快速的震后滑坡制图对救灾行动起着至关重要的作用。为了解决遥感传统像素级的变化检测方法的结果中大量过度识别,以尼泊尔首都加德满都为研究区,首先利用震前震后两期Landsat-8影像进行主成分变换,然后对变换后包含丰富特征信息的第一主成分(PC1)影像作变化检测,最后利用震后影像的第3主成分、NDVI(Normalized Difference Vegetation Index)、坡度等特征去除变化检测结果中的非滑坡地物。目视解译成果验证表明:基于主成分变换的滑坡识别方法能将研究区93.0%的滑坡识别出来,识别效果较好;滑坡主要发生在研究区东北方向的Sun Koshi河谷一带,主要地形坡度为[20°,50°)。提出的方法能较好地应用于地震引起的大范围滑坡识别,为震后救援和重建工作提供有力帮助。

The earthquake of Nepal in 2015 and its aftershocks caused many landslides with its enormous destruction posing huge potential threats to residential lives and properties in the affected regions. Rapid and accurate detection of post-earthquake landslide is in urgent demand. Traditional pixel-based change detection methods, however, delivered a large amount of over-recognized objects. In view of this, a principal component analysis (PCA) based change detection method was proposed to recognize post-earthquake landslides. Katmandu, the capital and largest city of Nepal, was selected as the study area. First of all, to remove noise and abundant information, an orthogonal transformation was applied to before-earthquake and post-earthquake Landsat-8 images of Katmandu respectively. In subsequence, converted set of features, as the first principal component (PC1), was used for change detection. Last but not the least, non-landslides were eliminated by NDVI, PC3 and slope feature from previous results. Validation of the detected results with high-resolution images from Google Earth shows that the proposed method is able to identify landslides with relatively high accuracy (93.0%). And it also proves the applicability of Landsat-8 satellite imagery for landslide mapping with its multispectral information. The post-earthquake landslides are generally found in areas of large surface slopes (between 20° and 50° ) of the Sun Koshi Valley, which is in the Northeast of the study area. The research findings suggest that the proposed method is effective in identifying post-earthquake landslides, thus assisting post-earthquake rescue and reconstruction.