4.7 Article

Persistent Scatterer Interferometry (PSI) Technique for the Identification and Monitoring of Critical Landslide Areas in a Regional and Mountainous Road Network

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REMOTE SENSING
卷 15, 期 6, 页码 -

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MDPI
DOI: 10.3390/rs15061550

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landslides; remote sensing; persistent scatterers; SAR; interferometry; GIS; spatial analysis; P-PSI; Sentinel-1; timeseries analysis

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A reliable road network is important for connecting communities and promoting economic growth. Traditional methods for identifying and monitoring landslides on complex road networks are time-consuming and resource-intensive. This study applied parallelized PSI (P-PSI) to quickly identify and monitor potential landslide areas in the Chania regional unit of Crete, Greece, providing a valuable tool for local stakeholders.
A reliable road network is a vital local asset, connecting communities and unlocking economic growth. Every year landslides cause serious damage and, in some cases, the full disruption of many road networks, which can last from a few days to even months. The identification and monitoring of landslides with conventional methods on an extended and complex road network can be a rather difficult process, as it requires a significant amount of time and resources. The road network of the Chania regional unit on the island of Crete in Greece is a typical example, as it connects, over long distances, many remote mountainous villages with other local communities, as well as with the main urban centers, which are mainly located across the shore. Persistent scatterer interferometry (PSI) is a remote-sensing technique that can provide a reliable and cost-effective solution, as it can be used to identify and monitor slow-moving and ongoing landslides over large and complex areas such as those of the mountainous road networks. This study applied PSI in the Chania regional unit, using the novel parallelized PSI (P-PSI) processing chain, developed by the Operational Unit Center for Earth Observation Research and Satellite Remote Sensing BEYOND of the Institute of Astronomy and Astrophysics, Space Applications and Remote Sensing of the National Observatory of Athens (BEYOND) for the rapid identification of the areas, most critical to landslide in a local road network. The application of P-PSI speeded up the total required processing time by a factor of five and led to the rapid identification and monitoring of 235 new slow-moving landslides. The identified landslides were correlated with a pre-existing landslide inventory and open access visual data to create a complete landslide inventory and a relative landslide inventory map, thus offering a valuable tool to local stakeholders.

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