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Landslide Studies Integrating Remote Sensing and Geophysical Data (Second Edition)

A Special Issue of Remote Sensing (ISSN 2072-4292) belonging to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: closed (31 May 2026) | Viewed by 1371

Editors


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Guest Editor
Department of Earth Sciences, University of Firenze, 50121 Firenze, Italy
Interests: exploration geophysics; landslides; engineering geology; resilience; natural hazards; remote sensing; seismics; earth sciences
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Guest Editor
Urban and Environmental Engineering, University of Liege, Liege, Belgium
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

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Guest Editor
Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
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

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.

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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.

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

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Published Papers (1 paper)

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Research

27 pages, 12831 KB  
Article
Integration of Infrared Thermography and GB-InSAR for Dynamic Monitoring of Rock Face Movements: Case Study of La Cornalle Cliff (Switzerland)
by Charlotte Wolff, Li Fei, Carlo Rivolta, Véronique Merrien-Soukatchoff, Marc-Henri Derron and Michel Jaboyedoff
Remote Sens. 2026, 18(10), 1534; https://doi.org/10.3390/rs18101534 - 12 May 2026
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Abstract
Rockfall events are significant natural hazards on fractured rock cliffs, often driven by environmental forcing, including thermal variations that induce stress and fatigue in rocks. This study presents the first application of Ground-Based Interferometric Synthetic Aperture Radar (GB-InSAR) for high-resolution monitoring of sub-millimeter [...] Read more.
Rockfall events are significant natural hazards on fractured rock cliffs, often driven by environmental forcing, including thermal variations that induce stress and fatigue in rocks. This study presents the first application of Ground-Based Interferometric Synthetic Aperture Radar (GB-InSAR) for high-resolution monitoring of sub-millimeter thermally induced displacements on a rock slope. An eight-day pilot experiment conducted at the La Cornalle molasse cliff (Vaud, Switzerland) revealed cyclic displacement signals with a clear 24 h periodicity, identified through Fourier and wavelet analyses, with a mean amplitude of 5 × 10−4 m. Simultaneously, infrared thermography (IRT) and a weather station recorded rock surface and air temperature variations, allowing a first estimation of the time lag between thermal forcing and mechanical response, with delays of 1–8 h relative to air temperature and 1–6 h relative to solar radiation. An analytical deformation model based on thermal diffusion predicts a daily displacement amplitude of 4.2 × 10−5 m, highlighting a significant difference with GB-InSAR observations and emphasizing the influence of structural complexity and thermo-hydro-mechanical processes in rock slopes. These results demonstrate the capability of combined high-resolution remote sensing techniques to quantify thermo-mechanical behavior in rock masses and provide a methodological framework for future investigations of rockfall-prone slopes. Full article
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