Satellite interferometric data for landslide intensity evaluation in mountainous regions

• Published in: International journal of applied earth observation and geoinformation Vol. 87; p. 102028
• Main Authors: Solari, Lorenzo, Bianchini, Silvia, Franceschini, Rachele, Barra, Anna, Monserrat, Oriol, Thuegaz, Patrick, Bertolo, Davide, Crosetto, Michele, Catani, Filippo
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-05-2020; Elsevier
• Subjects: Landslide intensity; Mountainous region; Potential loss; Satellite interferometry; Mountainous region; Satellite interferometry; Landslide intensity; Potential loss
• ISSN: 1569-8432; 1872-826X
• DOI: 10.1016/j.jag.2019.102028

•Satellite interferometric data as tools for landslide intensity estimation.•Intensity as input for landslide potential loss calculation.•Regional scale approach fully relying on interferometric data.•Combination of interferometric data and gravitational process models.
Multi-Temporal Interferometric Synthetic Aperture Radar (MTInSAR) data offer a valuable support to landslide mapping and to landslide activity estimation in mountain environments, where in situ measures are sometimes difficult to gather. Nowadays, the interferometric approach is more and more used for wide-areas analysis, providing useful information for risk management actors but at the same time requiring a lot of efforts to correctly interpret what satellite data are telling us. In this context, hot-spot-like analyses that select and highlight the fastest moving areas in a region of interest, are a good operative solution for reducing the time needed to inspect a whole interferometric dataset composed by thousands or millions of points. In this work, we go beyond the concept of MTInSAR data as simple mapping tools by proposing an approach whose final goal is the quantification of the potential loss experienced by an element at risk hit by a potential landslide. To do so, it is mandatory to evaluate landslide intensity. Here, we estimate intensity using Active Deformation Areas (ADA) extracted from Sentinel-1 MTInSAR data. Depending on the localization of each ADA with respect to the urban areas, intensity is derived in two different ways. Once exposure and vulnerability of the elements at risk are estimated, the potential loss due to a landslide of a given intensity is calculated. We tested our methodology in the Eastern Valle d’Aosta (north-western Italy), along four lateral valleys of the Dora Baltea Valley. This territory is characterized by steep slopes and by numerous active and dormant landslides. The goal of this work is to develop a regional scale methodology based on satellite radar interferometry to assess the potential impact of landslides on the urban fabric.