Landslide Studies Integrating Remote Sensing and Geophysical Data

Dear Colleagues,

Landslide investigation and monitoring is increasingly combining inputs from remotely sensed (RS), ground-based, and subsurface data. RS (optical, InSAR, UAV) and geophysical data (electrical, seismic, seismological and electro-magnetic, and 1-/2-/3-D surveys, as well as borehole information) 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 and geophysical data, also because of the different scales on which the landslides are generally studied when using these methods, spanning from a regional/wide 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. Standard visualisation tools (using combined map and section views, as well as animation of models) may not be sufficient to get a deeper insight into the structure and, even more importantly for active landslides, into the dynamics of failure processes. Emerging extended (Virtual) reality (XR) technologies (that have already been used for quite some time in other geoscience fields, mostly those related to exploitation, but less in geohazard research) may help to overcome difficulties of complex model visualisation and interpretation.

Sincerely

Dr. Hans-Balder Havenith
Dr. Romy Schlögel
Dr. Francesca Cigna
Dr. Veronica Pazzi
Dr. Marc-Henri Derron
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.