Time-Series Remote Sensing for Geohazard Monitoring and Early Warning
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: 30 April 2026 | Viewed by 12
Special Issue Editors
Interests: geohazards; remote sensing; artificial intelligence; geomechanics
Interests: landslide mapping; susceptibility; disaster mitigation
Interests: landslide detection; landslide monitoring and early warning; InSAR
Special Issues, Collections and Topics in MDPI journals
Interests: geosystems engineering; artificial intelligence; geoinformatics; geostatistics; natural hazards; remote sensing; mineral exploration
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The increasing frequency and intensity of geohazards—such as landslides, earthquakes, volcanic activity, land subsidence, sinkholes, and glacier movements—demand robust monitoring and early warning systems. Advances in remote sensing now make it possible to observe Earth’s surface dynamics at unprecedented spatial and temporal scales. Time-series remote sensing, integrating continuous observations from SAR, optical, LiDAR, UAV, and GNSS data, enables the detection of subtle surface changes and precursory signals essential for understanding and forecasting geohazard processes.
This Special Issue aims to showcase innovative research and practical applications that advance the use of time-series remote sensing for geohazard monitoring and early warning. We encourage studies that develop or apply new algorithms, combine multi-sensor datasets, explore data fusion and machine learning, or demonstrate operational workflows for hazard detection and decision support. Both methodological developments and case studies from diverse geographic and hazard contexts are welcome.
Topics of interest include (but are not limited to):
- Time-series analysis and deformation modeling using SAR, optical, and LiDAR data;
- Multi-sensor and multi-temporal data fusion for geohazard assessment;
- Real-time and near-real-time geohazard monitoring and alerting systems;
- Detection of precursory signals and change-point analysis;
- Machine learning and AI for geohazard pattern recognition and forecasting;
- Integration of remote sensing data with in situ measurements and physical models;
- Uncertainty assessment and validation of time-series deformation results;
- Case studies on any specific type of ground failure, such as landslides, sinkholes, and liquefaction.
This Special Issue seeks to build a bridge between scientific innovation and operational implementation, advancing the role of remote sensing in reducing geohazard risks and enhancing early warning capabilities worldwide.
Dr. Weiwei Zhan
Dr. Yunus Ali Pulpadan
Prof. Dr. Weile Li
Dr. Adel Asadi
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
- time-series remote sensing
- geohazard monitoring
- early warning systems
- multi-sensor data fusion
- machine learning
- InSAR
- LiDAR
- disaster risk reduction
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