Abstract
In recent years, heavy rain become more severe and frequent in Japan and cause tremendous damage to various infrastructures. For example, the expressways are exposure to the landslides occurred in the surrounding mountainous areas after the heavy rain, and accordingly to the operation halt. In order to reduce the damage caused by such a large-scale disaster, predicting their occurrence in advance is desirable. In recent years, Synthetic Aperture Radar (SAR) imagery is expected to be used to understand ground deformation in an area and at low cost. In particular, Persistent Scatterers Interferometry SAR (PSInSAR), which utilizes multitemporal SAR images, can be used to monitor minute changes in ground deformation behavior. In contrast, depending on the land cover of areas, noise is generated during the analysis due to the backscattering instabilities. In this study, PSInSAR was applied to the area along the Takeo Junction (JCT) in western Japan, where a landslide occurred in the past due to a heavy rain and the road surface was uplifted significantly. Then, based on the estimated ground deformation, we conducted a basic study on the development of a noise-robust system to detect the signs of disaster. The results suggested that the proposed method could observe the signs of landslide disasters before they occur.
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