Intelligent Perception of Disaster Information in Remote Sensing Imagery
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 20 March 2025 | Viewed by 151
Special Issue Editors
Interests: remote sensing image processing; deep learning; fire detection; computer vision
Interests: 3D mapping; SLAM; computer vision
Special Issues, Collections and Topics in MDPI journals
Interests: natural hazards; remote sensing; climate change; GIS; water; disaster management; geology; geo-environmental issues; geography and environmental management
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, global climate change has increased the frequency of extreme weather events and natural disasters, such as floods, typhoons, earthquakes, landslides, and wildfires, posing significant threats to society, the economy, and the environment. Remote sensing technology, using platforms like satellites, drones, and aircraft, enables the real-time, wide-area acquisition of high-resolution data without physical contact. This allows for the rapid provision of dynamic, large-scale information across hazardous and widespread disaster areas, far surpassing the capabilities of traditional ground-based methods. Moreover, remote sensing can offer continuous time-series data at different stages of a disaster—before, during, and after—providing crucial insights for early warning, disaster assessment, and post-disaster recovery. However, the challenge remains in extracting valuable information from the vast, multi-source, and multi-scale data available. The rapid advancements in artificial intelligence and big data analytics are now offering strong support for the intelligent perception of remote sensing imagery, enhancing both the automation and accuracy of information extraction and enabling real-time monitoring and quick responses in critical moments.
This Special Issue aims to explore the latest research advancements and applications of remote sensing technology in the intelligent perception of disaster information, with a particular focus on the role of emerging technologies such as artificial intelligence and multi-source data fusion in disaster monitoring and management. This theme is closely aligned with the scope of the Remote Sensing journal, emphasizing innovative applications of remote sensing technology and promoting both academic and practical progress in this field.
Suggested themes：
- Natural disaster monitoring.
- AI-based disaster extraction.
- Multi-source data fusion.
- High-res imagery analysis.
- Real-time monitoring systems.
- Geospatial big data applications.
- Emerging tech in disaster management.
- Post-disaster recovery studies.
Dr. Yakun Xie
Dr. Shengjun Tang
Dr. Saeid Pirasteh
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
- disaster perception
- artificial intelligence
- multimodal data
- emergency rescue
- post-disaster reconstruction
- geospatial big data
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