Multiplatform and Multisensor Applications for Landslide Characterization and Monitoring

Dear Colleagues,

Nowadays, active landslides can be identified and monitored via several imaging platforms, ranging from terrestrial to crewed/uncrewed aerial vehicles or spaceborne satellites. Despite the imaging sensing method adopted, the scientific community has extensive options in terms of image processing algorithms, which have been developed to detect changes and/or derive spatially distributed displacements over time. The vast number of combinations of sensors and platforms, coupled with the significant range of geometric and temporal resolution, can lead to countless applications. Such tools, when integrated with ground truth datasets, increasingly provide new solutions for landslide monitoring and interpretation. Moreover, integrating these high-tech imaging and processing tools with rigorous ground truth datasets has revolutionized the methods via which landslides can be monitored and interpreted. Ground truth data provide a crucial baseline for validating remote sensing observations, ensuring both the precision and reliability of interpretations made using satellite and aerial imagery. The emerging insights gained from these integrated systems not only enhance our understanding of landslide dynamics but also substantially contribute to risk mitigation efforts. By providing early warning signals and facilitating proactive disaster management strategies, such tools are invaluable assets for guarding against the devastation commonly wrought by landslides. In this Special Issue, papers dealing with landslide characterization and monitoring and/or technical papers presenting innovative image processing algorithms applied to ground displacement analysis/observation are welcome. If potential authors wish to discuss any proposal, feel free to get in touch with this Special Issue’s Editorial Team.

Dr. Stratis Karantanellis
Dr. Marco Mulas
Dr. Giuseppe Ciccarese
Prof. Dr. Paolo Mazzanti
Guest Editors

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• landslide detection
• landslide characterization
• landslide monitoring
• data fusion
• remote sensing