Remote Sensing in Landslide Susceptibility Evaluation and Management
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 30 April 2026 | Viewed by 1
Special Issue Editors
Interests: natural hazards; water resources; machine learning; soft computing; GIS
Special Issues, Collections and Topics in MDPI journals
Interests: natural hazards; geoinformatics; machine learning; soft computing; GIS; remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: natural hazards; engineering geology, machine learning; soft computing; spatial analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Landslides represent one of the most frequent and destructive geological hazards worldwide, posing severe threats to human lives, infrastructure, and the environment. In recent years, the integration of remote sensing technologies with advanced modeling approaches has significantly improved landslide susceptibility evaluation and management. This Special Issue aims to highlight the latest advances, methodologies, and applications of remote sensing that contribute to understanding landslide-prone areas, identifying critical triggering factors, and supporting early warning and mitigation strategies.
We welcome original research articles and reviews covering a broad range of topics, including—but not limited to—multi-source remote sensing data fusion, landslide inventory mapping, machine learning-based susceptibility modeling, real-time monitoring systems, and the assessment of climate change impacts on landslide dynamics. Contributions that explore novel remote sensing techniques or present case studies with practical implications for risk reduction are particularly encouraged.
This Special Issue provides a timely platform for researchers, practitioners, and decision-makers to share innovations and insights that contribute to more effective and science-based landslide disaster risk management.
Dr. Haoyuan Hong
Dr. Paraskevas Tsangaratos
Dr. Ioanna Ilia
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 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 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
- landslide susceptibility
- remote sensing
- hazard assessment and monitoring
- early warning
- machine learning
- disaster risk management
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