Landslide Detection Using Machine and Deep Learning
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Earth Observation for Emergency Management".
Deadline for manuscript submissions: 28 November 2025 | Viewed by 14
Special Issue Editor
Interests: SAR; optical images; LiDAR data; disasters; building damage; bridge damage
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Due to global warming, the frequency of extreme weather events is increasing, leading to a higher risk of landslides. Traditional methods for landslide detection and monitoring, while important, often face limitations in scalability, accuracy, and efficiency. Recent advances in machine learning (ML) and deep learning (DL) offer promising alternatives by enabling the analysis of large-scale, multi-source data such as remote sensing imagery, digital elevation models, and sensor networks. These approaches can enhance early warning systems, risk assessment models, and real-time monitoring, contributing to more effective disaster risk reduction and emergency response strategies.
This Special Issue aims to compile studies that explore applications of machine learning and deep learning to facilitate landslide forecasting, monitoring and detection.
This Special Issue welcomes original research articles and comprehensive reviews on the application of ML and DL techniques for landslide detection and prediction. Topics of interest include, but are not limited to, the following:
- Landslide susceptibility mapping;
- Time series analysis for landslide forecasting;
- Remote sensing and image-based landslide detection;
- The integration of multi-source data (e.g., meteorological, geological, hydrological);
- Explainable AI and model interpretability in landslide studies;
- Real-time landslide monitoring with sensor and IoT data.
Dr. Wen Liu
Guest Editor
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 detection
- real-time monitoring
- time series analysis
- deep learning
- machine learning
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
