Landslide Studies Integrating Remote Sensing and Geophysical Data (Second Edition)
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 31 October 2024 | Viewed by 31
Special Issue Editors
Interests: exploration geophysics; landslides; engineering geology; resilience; natural hazards; remote sensing; seismics; earth sciences
Special Issues, Collections and Topics in MDPI journals
Interests: landslide investigation and modelling; applied geophysics; active and passive seismic methods; GIS analysis; 3D geomodelling; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: geophysical techniques (geoelectrical and seismic); hydrological processes; groundwater dynamics; slope instabilities; geophysical; environmental/hydrological data
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Landslide investigation and monitoring is increasingly combining inputs from remotely sensed (RS), ground-based, and subsurface data. RS (optical, InSAR, UAV), geophysical data (electrical, seismic, seismological and electro-magnetic, 1-/2-/3-D and 4-D surveys, as well as borehole information), and geotechnical data (such as inclinometer, tiltmeter, piezometer, strain gauges, etc.) together provide a more comprehensive view of those geohazard phenomena, especially if active mass movements are considered. However, often, these surveys are organised separately, and a full integration of the surface and subsurface information is barely performed. Most data representations lack a model that allows for the joint interpretation of RS, geophysical, and geotechnical data, also because of the different scales on which the landslides are generally studied when using these methods, spanning from a regional to local scale. Such models, e.g., based on 3D geomodelling, should also help better cross-validate RS, surface, and subsurface information. In particular, geophysical data interpretation can be affected by high levels of uncertainty—well-integrated and jointly modelled RS, surface, and geophysical data will likely help reduce this uncertainty.
Finally, for large mass movements or a group of investigated massive failures, the surface and subsurface models, even if well-constructed by integrating all processed inputs and outputs, are difficult to analyse and interpret as a whole because of the complexity of information included in the models. Emerging extended (Virtual) reality technologies that are established in some geoscience disciplines, are also emerging in landslide hazard analysis.
Given the great success of the previous volume, we are glad to announce this second Edition of the volume ‘Landslide Studies Integrating Remote Sensing and Geophysical Data’.
Dr. Veronica Pazzi
Dr. Anne-Sophie Mreyen
Dr. Sebastian Uhlemann
Guest Editors
Manuscript Submission Information
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Keywords
- joint remote sensing and geophysical surveys
- geophysical landslide monitoring
- 3D data integration models
- cross-validation of RS, ground-based, and subsurface information
- visualization in extended reality
