On July 6th and 7th, Jhonatan Rivera Rivera presented SARAI’s contribution at the IV Geomatic Engineering Congress “CIGEO 2023”. This congress provides a platform for doctoral candidates from the UPM-UPV Geomatic Engineering program to showcase progress in their doctoral theses and share their experiences with fellow researchers.
Our work, titled “Detection and Classification of Active Deformation Areas Based on SAR Data: A National Database for Natural and Induced Hazard Management. Application in Southeastern Spain,” introduces an innovative approach to automatically classify deformation processes using InSAR data and Machine Learning techniques based on decision trees and clustering. Our results demonstrate promising performance, with an AUC > 0.95, identifying several covariates of morphometric, geological, hydrogeological, and geotechnical nature as key factors. This automatic classification of InSAR data has significant implications for risk management related to land deformation, providing an indispensable tool for decision-makers in urban planning and land use management.