Post-failure landslide change detection is crucial for mitigation strategies. However, the methods used to investigate this issue all involve a tough workflow, and the free access Sentinel-2 satellite is underutilized. In this study, we use ten Sentinel-2 optical images to explore the effectiveness of using these images to detect post-landslide changes in the Huangnibazi landslide failure using an easy workflow. We found that the landslide can be qualitatively divided into a startup and acceleration stage, a front and lateral edge expansion stage, and a stabilization stage using time-series true color images. After the normalized difference vegetation index (NDVI) was calculated to identify landslide scars, which were validated using the unmanned aerial vehicle (UAV) orthoimages, we found that the same three change processes identified were also reflected by the landslide scar count change analysis in a quantitative way. Based on the three different stages, a red-green-blue (RGB) composite of the NDVI images was constructed and was found to reflect the different change period of the right and left landslide edges. Most importantly, the changes within a pixel unit were detected using an NDVI RGB composite with cold colors representing a retrogressive landslide mode. All of these findings indicate that the huge potential of the use of Sentinel-2 images in similar applications.

中文翻译：

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使用光学卫星 Sentinel-2 图像的故障后滑坡变化检测和分析

故障后滑坡变化检测对于缓解策略至关重要。然而，用于调查这个问题的方法都涉及一个艰难的工作流程，而且免费访问的 Sentinel-2 卫星没有得到充分利用。在这项研究中，我们使用 10 张 Sentinel-2 光学图像来探索使用这些图像使用简单的工作流程检测黄泥坝子滑坡破坏中滑坡后变化的有效性。我们发现滑坡可以定性地分为启动和加速阶段、前侧和横向边缘扩展阶段以及使用时间序列真彩色图像的稳定阶段。在计算归一化差异植被指数（NDVI）以识别滑坡疤痕后，使用无人机（UAV）正射影像进行验证，我们发现，滑坡疤痕计数变化分析也以定量的方式反映了所确定的相同的三个变化过程。基于三个不同的阶段，构建了 NDVI 图像的红绿蓝 (RGB) 复合图，发现其反映了左右滑坡边缘的不同变化周期。最重要的是，使用 NDVI RGB 复合材料检测像素单元内的变化，冷色代表回归滑坡模式。所有这些发现都表明在类似应用中使用 Sentinel-2 图像的巨大潜力。构建了 NDVI 图像的红绿蓝 (RGB) 合成图，发现其反映了左右滑坡边缘的不同变化周期。最重要的是，使用 NDVI RGB 复合材料检测像素单元内的变化，冷色代表回归滑坡模式。所有这些发现都表明在类似应用中使用 Sentinel-2 图像的巨大潜力。构建了 NDVI 图像的红绿蓝 (RGB) 合成图，发现其反映了左右滑坡边缘的不同变化周期。最重要的是，使用 NDVI RGB 复合材料检测像素单元内的变化，冷色代表回归滑坡模式。所有这些发现都表明在类似应用中使用 Sentinel-2 图像的巨大潜力。