Special Issue "Geospatial Techniques for Landslides and Erosion Studies: Data Capture, Monitoring, Analysis and Modelling"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Prof. Dr. Tomás Fernández
Guest Editor
Department of Cartographic, Geodetic and Photogrammetric Engineering, University of JaénCampus de las Lagunillas s/n, Edificio A3. 23071. Jaén (Spain)
Interests: remote sensing; geomatics; landslides; erosion; natural hazards
Special Issues and Collections in MDPI journals
Prof. Dr. Christian Conoscenti
Guest Editor
Department of Earth and Marine Sciences, University of Palermo, Via Archirafi 22, 90123 Palermo, Italy
Interests: soil erosion; gully erosion; landslide susceptibility; stochastic modeling of geomorphic processes; natural hazards
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

In recent decades, landslides and erosion studies have undergone a great amount of development with the application of geospatial techniques. Point data capture is addressed by means of different instruments, such as total station, GNSS and in situ sensors (movement, wetness, etc.), but also with LiDAR techniques, both terrestrial (TLS) and aerial (ALS), that allow the acquisition of massive point clouds. Meanwhile, images are captured from sensors and cameras on board of different platforms: terrestrial, unmanned aerial systems (UAS), aerial or satellites.

These point clouds and images are processed via different approaches based on conventional photogrammetry and computer vision methods, which allow the preparation of high-quality data for further analysis. Moreover, the repetition of data acquisition along time allows the monitoring of landslide and erosion processes regarding both geometric features (position, limits, displacements, etc.) and non-geometric information (soil properties, wetness, elements affected, etc.). Multispectral analyses (vegetation and water indexes, classifications and object-based methods) complete the techniques used for landslide inventories and factors modelling.

Meanwhile, geospatial analysis and modelling in GIS environments are addressed to the scientific knowledge of landslide and erosion processes, and especially to the assessment of hazard and risk. Thus, susceptibility modelling, very useful in these processes, is performed by different techniques, from index-based methods to multivariate statistics methods (linear o logistic regression, discriminant analysis, etc.), machine learning methods (decision trees, random forest, support vector machines, etc.) or deep learning methods (neural networks). Hazard also includes time series analysis and predictive modelling, and risk considers engineering and economic information.

Therefore, we encourage scientists and experts in different disciplines to send their contributions to this Special Issue on topics focused on the application of geospatial techniques for landslides and erosion studies. These include data capture, monitoring, analysis and modeling of both landslides (shallow and deep landslides), and erosion (laminar and gully erosion).

Prof. Dr. Tomás Fernández
Prof. Dr. Christian Conoscenti
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 papers will be 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 100 words) can be sent to the Editorial Office for announcement on this website.

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 2400 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.


  • Landslides
  • Erosion
  • Gully erosion
  • Optical remote sensing
  • InSAR
  • Photogrammetry
  • LiDAR
  • Monitoring
  • Risk analysis
  • Machine learning
  • Modeling

Published Papers

This special issue is now open for submission.
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