Multi-Source Remote Sensing Integrations in Geological Hazards Research
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: 29 October 2025 | Viewed by 74
Special Issue Editors
Interests: mathematical geology; remote sensing of resources and environment; mineral resources exploration; geological big data integration applications
Interests: remote sensing geology; hyperspectral remote sensing and microwave remote sensing; remote sensing big data processing and integrated applications
Interests: earthquake forecasting; statistical seismology; earthquake precursor; AI-based earthquake forecasting
Special Issue Information
Dear Colleagues,
Due to various geological processes, geological hazards and their secondary effects generally involve crustal movements, topographic changes, and the instability of geological structures, such as landslides, mudslides, ground collapses, earthquakes, etc. Under the combined effects of global climate change and extensive anthropogenic activities, geological hazards pose an aggravating negative impact on human life, property, and environment. In order to effectively reduce disaster-related risks, it is vital to perform geohazard modeling, analysis, prediction, and assessment. In the fields of geological hazards, multi-source remote sensing (RS) data possess the benefits of large spatial coverage, frequent temporal updates, superior monitoring accuracy, and advanced modeling and analysis.
Multi-source remote sensing (RS) integration promotes accuracy and efficiency in geohazard monitoring, forecasting, and assessment by combining optical, radar (synthetic aperture radar, SAR), LiDAR, thermal infrared, and other RS data to achieve information reciprocity at the data, feature, or decision levels. With a focus on developing novel data fusion methods or applying multi-source RS data to investigate the process of geological structure and surface variations, it is crucial to advance the understanding of geohazard formation mechanisms underlying the Earth’s dynamic systems. Given the abundance of information derived from multi-source RS data, researchers can make theoretical or technical contributions to geohazard assessment and secondary disaster warnings, as well as to regional sustainable development, which is in line with this journal’s scope.
Therefore, this Special Issue is dedicated to exploring innovative data fusion methods or multi-source RS applications in geological hazard research. Both review articles and research articles are encouraged.
Dr. Jie Zhao
Dr. Shufang Tian
Dr. Ying Zhang
Dr. Die Hu
Guest Editors
Manuscript Submission Information
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Keywords
- data fusion
- landslide
- mudslide
- ground collapse
- earthquake
- hazard monitoring
- hazard assessment
- hazard prediction
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