The European Ground Motion Service (EGMS) delivers high-resolution information on ground motion over the European continent, by adopting Advanced Differential Interferometric Synthetic Aperture Radar (A-DInSAR) providing extensive datasets that include time series displacement data and associated velocity. However, the large volume of data can pose challenges for their analysis, particularly in studies covering extensive areas. To address this issue, a semi-automated method has been developed to identify and rank clusters of active deformation zones. This method consists of three key components: (1) the selection of landslide candidates, focused on identifying Areas of Interest (AOIs) based on the distribution of Persistent Scatterers derived from A-DInSAR analysis; (2) ranking the intensity and exposure levels associated with each landslide candidate for hazard and risk evaluations; and (3) in situ validation to evaluate the effectiveness of the methodology. The regional ranking of landslides facilitates the identification of AOIs where monitoring efforts should be prioritized or further investigations planned, particularly when these areas pose risks to infrastructure and urbanized regions. This approach supports the development of an operational service tailored to regional landslide risk mitigation, enabling the refinement of landslide catalogues by improving the delineation of landslide perimeters and assessing their current activity status. The AOIs distribution pointed out the impact on the study of the Lazio region, shedding light on the consistency of PAI Hazard maps, the landslide catalogue completeness, and the needs in frequent updates of such products. Additionally, the annual updates of EGMS products will allow regional authorities to continuously enhance and refine their landslide risk assessments.

Semi-automatic ranking of landslide candidate areas at a regional scale using EGMS InSAR data for territorial planning and risk management / Marmoni, Gian Marco; Antonielli, Benedetta; Caprari, Patrizia; Di Renzo, Maria Elena; Marini, Roberta; Mastrantoni, Giandomenico; Mazzanti, Paolo; Patelli, Davide; Bozzano, Francesca. - In: LANDSLIDES. - ISSN 1612-510X. - 22:12(2025), pp. 4077-4095. [10.1007/s10346-025-02597-6]

Semi-automatic ranking of landslide candidate areas at a regional scale using EGMS InSAR data for territorial planning and risk management

Marmoni, Gian Marco
;
Antonielli, Benedetta;Caprari, Patrizia;Di Renzo, Maria Elena;Marini, Roberta;Mastrantoni, Giandomenico;Mazzanti, Paolo;Patelli, Davide;Bozzano, Francesca
2025

Abstract

The European Ground Motion Service (EGMS) delivers high-resolution information on ground motion over the European continent, by adopting Advanced Differential Interferometric Synthetic Aperture Radar (A-DInSAR) providing extensive datasets that include time series displacement data and associated velocity. However, the large volume of data can pose challenges for their analysis, particularly in studies covering extensive areas. To address this issue, a semi-automated method has been developed to identify and rank clusters of active deformation zones. This method consists of three key components: (1) the selection of landslide candidates, focused on identifying Areas of Interest (AOIs) based on the distribution of Persistent Scatterers derived from A-DInSAR analysis; (2) ranking the intensity and exposure levels associated with each landslide candidate for hazard and risk evaluations; and (3) in situ validation to evaluate the effectiveness of the methodology. The regional ranking of landslides facilitates the identification of AOIs where monitoring efforts should be prioritized or further investigations planned, particularly when these areas pose risks to infrastructure and urbanized regions. This approach supports the development of an operational service tailored to regional landslide risk mitigation, enabling the refinement of landslide catalogues by improving the delineation of landslide perimeters and assessing their current activity status. The AOIs distribution pointed out the impact on the study of the Lazio region, shedding light on the consistency of PAI Hazard maps, the landslide catalogue completeness, and the needs in frequent updates of such products. Additionally, the annual updates of EGMS products will allow regional authorities to continuously enhance and refine their landslide risk assessments.
2025
EGMS; automatic selection; intensity ranking; interferometry; landslide candidates; landslide risk
01 Pubblicazione su rivista::01a Articolo in rivista
Semi-automatic ranking of landslide candidate areas at a regional scale using EGMS InSAR data for territorial planning and risk management / Marmoni, Gian Marco; Antonielli, Benedetta; Caprari, Patrizia; Di Renzo, Maria Elena; Marini, Roberta; Mastrantoni, Giandomenico; Mazzanti, Paolo; Patelli, Davide; Bozzano, Francesca. - In: LANDSLIDES. - ISSN 1612-510X. - 22:12(2025), pp. 4077-4095. [10.1007/s10346-025-02597-6]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1757413
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