Advanced Geoinformatics and Remote Sensing Technologies for Early Warning and Disaster Management
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".
Deadline for manuscript submissions: 31 October 2025 | Viewed by 330
Special Issue Editors
Interests: virtual geographic environments; geovisualization for disaster management; machine learning for geoinformation
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing and machine learning for building reconstruction, urban informatics, and disaster management
Interests: remote sensing for traffic and disaster management; machine learning for geoinformation
Special Issue Information
Dear Colleagues,
Over the past few decades, extreme natural hazards have become more frequent as a result of climate change, posing serious challenges to disaster prevention and mitigation. The development of Earth observation, particularly advanced remote sensing and geoinformatics technologies, has played a pivotal role in identifying the causes, patterns, processes, and impacts of disasters, significantly enhancing early warning and disaster management.
In this context, this Special Issue aims to explore the application of advanced remote sensing technologies (e.g., InSAR, LiDAR) and geoinformatics (e.g., Internet of Things, Digital Twins) in early warning and disaster management, as well as the use of machine learning algorithms in these areas. Research and solutions will address global, regional, and local concerns related to early hazard detection, spatiotemporal process modeling, and damage assessment, ultimately strengthening the environment and enhancing community resilience. Topics for this Special Issue include, but are not limited to, the following:
- IoT and DT for disaster early warning;
- Hazard, risk, and vulnerability assessment;
- Rapid damaged building detection;
- Multi-dimensional visualization;
- Big data analytics in disaster risk reduction;
- Social media insights on disaster perception;
- Advanced machine learning algorithms for hazard detection.
Dr. Weilian Li
Dr. Yao Sun
Dr. Nina Merkle
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
- geoinformatics
- remote sensing
- disaster management
- early warning
- resilience and environment sustainability
- GeoAI
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