Abstract
Slow deep-seated mass movements are widespread players of slope dynamics, with different mechanisms depending on involved materials, geomorphic settings and external forcing. Alpine settings are extensively affected by slow rock-slope deformations, deep-seated rockslides and periglacial features (e.g. rock glaciers). Mountains with fluvial-dominated topography in sedimentary rocks (i.e. Apennines) are typically affected by long-lived earthflows. These processes have different controls, show different spatio-temporal deformation patterns and rates, and threaten lives, activities, and infrastructures in different ways. Mitigating risks posed by deep-seated mass movements requires capabilities to: a) detect and classify different processes systematically and rapidly over wide areas; b) monitor their evolution towards possible destabilization; c) predict interactions with elements at risk. Current regional scale analyses rely on geomorphological techniques supported by remote sensing to capture processes and their spatio-temporal evolution. These approaches are accurate but time consuming and difficult to update. Such gaps could be filled using artificial intelligence techniques, yet their applications to mass movements are still few, mostly limited to interpretation of optical images and missing robust process-oriented approaches. The MIRAGE project will exploit the complementary expertise of three research units to combine multi-scale geomorphological data, spaceborne InSAR and deep learning techniques. The project aims at developing innovative, objective and semi-automated methods to detect and classify slow mass movements on wide areas based on remotely sensed information. The construction of libraries of expert-interpreted InSAR phase signal features, corresponding to
Dettagli del progetto
Responsabile scientifico: Alessandro Simoni
Strutture Unibo coinvolte:
Dipartimento di Scienze Biologiche, Geologiche e Ambientali
Coordinatore:
Università degli Studi di MILANO-BICOCCA(Italy)
Contributo totale Unibo: Euro (EUR) 78.861,00
Durata del progetto in mesi: 24
Data di inizio
28/09/2023
Data di fine:
28/02/2026
