Slow moving landslides affect many regions across the world and their effects and occurrence has increased recently due to the effects of climate change and human development. Thus, it is necessary to develop new methodology to assess the state of activity of slow-moving landslides. In this framework, this study proposes a new comprehensive methodology that integrates the most recent displacement information from Sentinel-1 (EGMS, 2018-2022 and 2019-2023) with topography (DTM), land cover map, geological map, landslide inventory and previous missions (ERS-1/2 1992-2000, and Radarsat-1 2003-2010). The preprocessing of the datasets allowed to validate the usage of the EGMS datasets as a reliable source of information for the monitoring of slow moving landslide activity. The study combinespre and post processing methodologies of already-processed InSAR dataset (Visibility, Suitability, Velocity along the slope, Homogeneity Index) and the recently developed geospatial analysis tools (Active Displacement Areas) to improve the understanding of the extent of slow-moving landslides. The methodology is applied to the Oltrepò Pavese, an area prone to landslides in northern Italy. The main result of the study is the reevaluation of state of activity of the landslide inventory by comparing the obtained results from Sentinel-1 (EGMS) and Radarsat-1/2 datasets, with a total of 218 and 132 landslides to be reclassified as active and reactivated respectively. Additionally, the obtained active displacement areas were compared to the information in the landslide inventory to suggest areas in which additional in-depth analysis in recommended. These findings suggest possible changes in the extent of landslides underlining the importance of InSAR data for land use planning mostly in area where no in-situ monitoring systems are available.

Slow moving landslides affect many regions across the world and their effects and occurrence has increased recently due to the effects of climate change and human development. Thus, it is necessary to develop new methodology to assess the state of activity of slow-moving landslides. In this framework, this study proposes a new comprehensive methodology that integrates the most recent displacement information from Sentinel-1 (EGMS, 2018-2022 and 2019-2023) with topography (DTM), land cover map, geological map, landslide inventory and previous missions (ERS-1/2 1992-2000, and Radarsat-1 2003-2010). The preprocessing of the datasets allowed to validate the usage of the EGMS datasets as a reliable source of information for the monitoring of slow moving landslide activity. The study combinespre and post processing methodologies of already-processed InSAR dataset (Visibility, Suitability, Velocity along the slope, Homogeneity Index) and the recently developed geospatial analysis tools (Active Displacement Areas) to improve the understanding of the extent of slow-moving landslides. The methodology is applied to the Oltrepò Pavese, an area prone to landslides in northern Italy. The main result of the study is the reevaluation of state of activity of the landslide inventory by comparing the obtained results from Sentinel-1 (EGMS) and Radarsat-1/2 datasets, with a total of 218 and 132 landslides to be reclassified as active and reactivated respectively. Additionally, the obtained active displacement areas were compared to the information in the landslide inventory to suggest areas in which additional in-depth analysis in recommended. These findings suggest possible changes in the extent of landslides underlining the importance of InSAR data for land use planning mostly in area where no in-situ monitoring systems are available.

Assessment of the State of Activity in Slow-Moving Landslides through the EGMS InSAR products: The Case Study of Oltrepò Pavese

SANCHEZ CARRASCO, AUGUSTO GONZALO
2024/2025

Abstract

Slow moving landslides affect many regions across the world and their effects and occurrence has increased recently due to the effects of climate change and human development. Thus, it is necessary to develop new methodology to assess the state of activity of slow-moving landslides. In this framework, this study proposes a new comprehensive methodology that integrates the most recent displacement information from Sentinel-1 (EGMS, 2018-2022 and 2019-2023) with topography (DTM), land cover map, geological map, landslide inventory and previous missions (ERS-1/2 1992-2000, and Radarsat-1 2003-2010). The preprocessing of the datasets allowed to validate the usage of the EGMS datasets as a reliable source of information for the monitoring of slow moving landslide activity. The study combinespre and post processing methodologies of already-processed InSAR dataset (Visibility, Suitability, Velocity along the slope, Homogeneity Index) and the recently developed geospatial analysis tools (Active Displacement Areas) to improve the understanding of the extent of slow-moving landslides. The methodology is applied to the Oltrepò Pavese, an area prone to landslides in northern Italy. The main result of the study is the reevaluation of state of activity of the landslide inventory by comparing the obtained results from Sentinel-1 (EGMS) and Radarsat-1/2 datasets, with a total of 218 and 132 landslides to be reclassified as active and reactivated respectively. Additionally, the obtained active displacement areas were compared to the information in the landslide inventory to suggest areas in which additional in-depth analysis in recommended. These findings suggest possible changes in the extent of landslides underlining the importance of InSAR data for land use planning mostly in area where no in-situ monitoring systems are available.
2024
Assessment of the State of Activity in Slow-Moving Landslides through the EGMS InSAR products: The Case Study of Oltrepò Pavese
Slow moving landslides affect many regions across the world and their effects and occurrence has increased recently due to the effects of climate change and human development. Thus, it is necessary to develop new methodology to assess the state of activity of slow-moving landslides. In this framework, this study proposes a new comprehensive methodology that integrates the most recent displacement information from Sentinel-1 (EGMS, 2018-2022 and 2019-2023) with topography (DTM), land cover map, geological map, landslide inventory and previous missions (ERS-1/2 1992-2000, and Radarsat-1 2003-2010). The preprocessing of the datasets allowed to validate the usage of the EGMS datasets as a reliable source of information for the monitoring of slow moving landslide activity. The study combinespre and post processing methodologies of already-processed InSAR dataset (Visibility, Suitability, Velocity along the slope, Homogeneity Index) and the recently developed geospatial analysis tools (Active Displacement Areas) to improve the understanding of the extent of slow-moving landslides. The methodology is applied to the Oltrepò Pavese, an area prone to landslides in northern Italy. The main result of the study is the reevaluation of state of activity of the landslide inventory by comparing the obtained results from Sentinel-1 (EGMS) and Radarsat-1/2 datasets, with a total of 218 and 132 landslides to be reclassified as active and reactivated respectively. Additionally, the obtained active displacement areas were compared to the information in the landslide inventory to suggest areas in which additional in-depth analysis in recommended. These findings suggest possible changes in the extent of landslides underlining the importance of InSAR data for land use planning mostly in area where no in-situ monitoring systems are available.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14239/33619