Updating Active Deformation Inventory Maps in Mining Areas by Integrating InSAR and LiDAR Datasets

Slope failures, subsidence, earthworks, consolidation of waste dumps, and erosion are typical active deformation processes that pose a significant hazard in current abandoned mining areas, given their considerable potential to produce damage affect the population at large. This work proves exploiting space-borne InSAR airborne LiDAR techniques, combined with data inferred through simple slope stability geotechnical model, obtain update inventory maps deformations areas. The proposed approach is illustrated by analyzing region Sierra de Cartagena-La Union (Murcia), mountainous area southeast Spain. Firstly, we processed Sentinel-1 imagery acquired both ascending descending orbits covering period from October 2016 November 2021. obtained velocities were then separately post-processed semi-automatically generate two areas (ADA) using ADATool. Subsequently, PS-InSAR LOS displacements tracks decomposed into vertical east-west components. Complementarily, open-access, non-customized point clouds used analyze surface changes movements. Furthermore, safety factor (SF) map was over study adopting infinite model. Finally, InSAR-derived maps, LiDAR-derived map, SF integrated previously published landslides’ perform preliminary classification different support optical images geological map. level activity index defined state reliability detected ADA. A total 28, 19, 5, 12 ADAs identified ascending, descending, horizontal, datasets, respectively, 58 change detection subsequent ADA enabled identification eight 11 zones which earthworks performed, three affected processes, 17 landslides, subsidence zone, seven compound 23 possible false positive ADAs. results highlight effectiveness these remote sensing techniques (i.e., LiDAR) conjunction models orthophotos information zones.