The cloud-free, wide-swath, day-and-night observation capability of synthetic aperture radar (SAR) has an important role in rapid landslide monitoring to reduce economic and human losses. Although interferometric SAR (InSAR) analysis is widely used to monitor landslides, it is difficult to use that for rapid landslide detection in mountainous forest areas because of significant decorrelation. We combined polarimetric SAR (PolSAR), InSAR, and digital elevation model (DEM) analysis to detect landslides induced by the July 2017 Heavy Rain in Northern Kyushu and by the 2018 Hokkaido Eastern Iburi Earthquake. This study uses fully polarimetric L-band SAR data from the ALOS-2 PALSAR-2 satellite. The simple thresholding of polarimetric parameters (alpha angle and Pauli components) was found to be effective. The study also found that supervised classification using PolSAR, InSAR, and DEM parameters provided high accuracy, although this method should be used carefully because its accuracy depends on the geological characteristics of the training data. Regarding polarimetric configurations, at least dual-polarimetry (e.g., HH and HV) is required for landslide detection, and quad-polarimetry is recommended. These results demonstrate the feasibility of rapid landslide detection using L-band SAR images.

中文翻译：

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使用偏振测量法和干涉相干法在山地森林地区检测滑坡

合成孔径雷达（SAR）的无云、宽幅、昼夜观测能力在快速滑坡监测、减少经济和人员损失方面具有重要作用。尽管干涉SAR（InSAR）分析被广泛用于监测滑坡，但由于显着的去相关性，很难将其用于山地森林地区的快速滑坡检测。我们结合极化 SAR (PolSAR)、InSAR 和数字高程模型 (DEM) 分析来检测由 2017 年 7 月九州北部大雨和 2018 年北海道伊武里东部地震引起的滑坡。本研究使用来自 ALOS-2 PALSAR-2 卫星的全极化 L 波段 SAR 数据。极化参数（α角和泡利分量）的简单阈值被发现是有效的。该研究还发现，使用 PolSAR、InSAR 和 DEM 参数的监督分类提供了很高的准确度，但应谨慎使用该方法，因为其准确度取决于训练数据的地质特征。关于极化配置，滑坡检测至少需要双极化（例如，HH 和 HV），建议使用四极化。这些结果证明了使用 L 波段 SAR 图像进行快速滑坡检测的可行性。