Development and Implementation of Early Detection and Warning Methods for Natural Hazards Utilizing Multi-Source Remote Sensing Data
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: 31 January 2026 | Viewed by 1221
Special Issue Editors
Interests: monitoring and early warning for natural disasters; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: snow-related disasters; artificial intelligence; numerical model
Interests: multi-source data analysis; remote sensing of environment
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The early identification and warnings of natural disasters are important foundations for disaster prevention and reduction. Multi-source remote sensing is a crucial means for rapidly detecting disaster hazards in a region and serves as a key source for extracting disaster warning information. Therefore, it is essential to promote the development and application of early identification and warning methods for natural disasters based on multi-source remote sensing data.
The purpose of this Special Issue is to publish high-quality research articles and reviews that show worldwide advances in remote sensing-based early detection and warning methods for natural hazards, including, but not limited to, the following issues:
- AI-based early and rapid identification of natural disasters.
- Estimation of material sources of debris flows.
- Early identification of disasters related to frozen soil, snow, fire, glaciers, or glacial lakes.
- Application of satellite-based rainfall and soil moisture monitoring in early warnings of flash floods, debris flows, landslides, and droughts.
- Application of reanalysis data, including remote sensing data, in the early identification and warnings of natural disasters.
- Multi-scale feasibility of applying remote sensing products in the early identification and warnings of disasters.
Dr. Shuang Liu
Dr. Zhipeng Xie
Dr. Bin Liu
Dr. Yuxia Li
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
- remote sensing
- reanalysis data
- method development
- natural hazards
- early identification
- monitoring and early warnings
- glacier-related disasters
- hill fire monitoring
- flash flood
- debris flow
- drought
- landslides
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