Remote sensing and geophysical surveying are potentially complementary and offer a possibility to arrange a suitable combination of applications to effectively infer and correlate surface/subsurface information. Even though these techniques have been applied in studies of landslides and unstable slopes for a few decades, it appears that their potential to provide integrated information with respect to that gained through direct, and generally more costly engineering geology investigations, has not always been fully exploited.
The progress in digital photogrammetry and cartography, in GPS surveying, in multi-temporal Synthetic Aperture Radar differential interferometry (DInSAR), the availability of high spatial resolution airborne or terrestrial LIDAR data, optical and radar satellite imagery, as well as future launches of sophisticated satellite systems (e.g. SENTINEL), hold the premise for ever increasing use of remote sensing and Earth Observation (EO) data in landslide investigations. In particular, it is expected that the exploitation of data from new radar sensors suitably integrated with GPS, laser scanner and in situ information will improve significantly our current capabilities to detect and monitor ground deformations related to slope instability phenomena. Similarly, the progress in geophysical data processing and interpretation methods and the exponential increase of power/cost ratio of computing tools, make now largely affordable frequent employment of sophisticated techniques like seismic reflection, surface waves analysis and tomography (both seismic and electrical), before generally reserved to academic communities and high-budget industrial applications.
This session is intended to: firstly, provide an overview of the advantages and limitations of conventional air- and space-borne EO applications, as well as of surface- and borehole-based geophysical information for landslide investigations; secondly, focus on innovative and potential applications of remote sensing and geophysical surveying for improved landslide and unstable slope assessments; thirdly, focus on data integration issues and development of cross-validation methods needed to exploit most profitably ground, air and EO data.