SAR Imagery for Landslide Detection and Prediction

Dear Colleagues,

In recent decades, satellite remote sensing has been established to measure surface displacements due to natural and human-induced processes. This tool has been improved with the synthetic aperture radar (SAR) technique. Thanks to this technique, millimetric–centimetric ground deformations can be measured, furnishing a fundamental tool for detecting and monitoring ground surface deformations related to landslides and for studying the trends of evolution of these phenomena.

SAR-based techniques have also been developed for the identification of landslides triggered in consequence of a particular event, allowing to create inventories and databases, overcoming the intrinsic limitation of the traditionally used optical images due to the cloud cover.

In this context, the launch in April 2014 of the first Sentinel-1 satellite and the other missions scheduled in the following years opened new frontiers for SAR image exploitation, increasing the temporal and spatial resolutions of deformation time-series and the ground response in terms of radar coherence for detecting new events and monitoring the evolution of slope instabilities at both regional and local scales.

This Special Issue aims at collecting new developments and methodologies, best practices, and applications of SAR imagery for the detection of landslides, the characterization of landslide displacements, and the prediction of new landslides triggering or of the evolution of displacement trends.

Without constraining the range of topics that are potentially suitable for inclusion in the Special Issue, we provide the following as examples:

- Methodologies to process SAR products for landslides detection, characterization, and prediction;

- Methods established for the detection of new landslides and for the creation of inventories and databases exploiting SAR images;

- Use of displacement time-series obtained through SAR techniques for the characterization of landslide kinematic behaviors;

- Models of prediction of landslides triggering using SAR images;

- Estimation of landslides state of activity using multitemporal SAR data;

- Prediction of the evolution in landslide displacements since the analyses of deformation time-series obtained through SAR;

- Identification of precursors and early detection of the triggering moment of catastrophic slope failures;

- Hazard assessment and early-warning strategies implemented through SAR data.

Dr. Massimiliano Bordoni
Prof. Claudia Meisina
Dr. Roberta Bonì
Guest Editors

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