Remote Sensing and GIScience for Natural Hazard Mitigation and Resilience
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".
Deadline for manuscript submissions: 28 September 2025 | Viewed by 213
Special Issue Editors
Interests: radar, optical, and thermal remote sensing, with a major specialization in synthetic aperture radar interferometry (InSAR); digital image processing and machine learning; geographic information systems (GIS); global navigation satellite systems (GNSS); crustal deformation modeling; geohazard assessment
Interests: multi-scale remote sensing of agriculture; crop suitability and sustainability; environmental niche modeling of plants and disease vectors; flood hazard vulnerability and impacts on land-use/land cover; cloud-based geoprocessing and digital cartography
Interests: land cover and land-use change; land–atmosphere interactions; remote sensing of agriculture; geospatial analysis of air quality and human health
Interests: remote sensing; GIS; LiDAR; drone; image processing; big data analysis; supercomputing; numerical analysis; data assimilation; hydrogeology; subsurface characterization; terrestrial biosphere modeling; carbon cycle; climate change
Special Issue Information
Dear Colleagues,
Natural hazards endanger human life, infrastructure, and ecosystems worldwide. As their frequency and intensity increase due to climate change and population growth in vulnerable regions, the need for effective mitigation and resilience-building measures becomes more pressing. These disasters cause billions in economic losses annually and displace millions, disproportionately affecting resource-limited communities. Remote sensing and geographic information science (GIScience) provide essential tools to address these challenges, offering unique capabilities to monitor, analyze, and respond to such events. Advances in machine learning, artificial intelligence, and big data analytics enhance these technologies, enabling real-time monitoring and predictive modeling, which are crucial for early warning systems and adaptive management. By providing timely, spatially explicit data and advanced analytical frameworks, they enable scientists, policymakers, and emergency responders to understand hazard dynamics, assess risks, and develop strategies for disaster preparedness, response, and recovery.
The aim of this Special Issue is to advance the use of remote sensing and GIScience in mitigating natural hazards and enhancing resilience through innovative research, methodologies, and practical applications. We seek high-quality studies showing how these technologies improve disaster preparedness, response, recovery, and risk management.
This Special Issue aligns with the scope of Remote Sensing, which advances remote sensing technologies to study Earth’s physical, biological, and human systems. The journal emphasizes data from satellites, aircraft, and other platforms to address global challenges, including environmental monitoring, resource management, and disaster management. Natural hazards and resilience are central to this scope, depending on remotely sensed data to monitor processes, map vulnerabilities, and inform decisions. By focusing on remote sensing and GIScience in disaster mitigation, this Special Issue supports the journal’s mission to promote innovative geospatial solutions to societal and environmental issues.
For this Special Issue of Remote Sensing, we invite contributions (research articles, reviews, technical notes, and case studies) exploring the critical role of remote sensing and GIScience in mitigating natural hazards and strengthening societal resilience. We particularly encourage submissions on disaster response, recovery strategies, and risk assessment, especially those with case studies from recent events. These contributions will deepen our understanding of how geospatial technologies can tackle the growing challenges of natural disasters, fostering a more resilient and sustainable future.
Prof. Dr. Mohamed Aly
Dr. Brad Peter
Dr. Yaqian He
Dr. Kashif Mahmud
Guest Editors
Dr. Abdullah Al Saim
Guest Editor Assistant
Institutional information: Arkansas Department of Transportation, 10324 Interstate 30, Little Rock, AR 72209, USA
E-Mail: AbdullahAl.Saim@ardot.gov
Webpage: https://abdullahalsaim.github.io/
Research Interests: forest dynamics; above-ground biomass estimation; satellite data fusion; wildfire susceptibility analysis; machine learning; remote sensing for ecosystem monitoring and conservation
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
- GIScience
- natural hazards
- disaster mitigation
- resilience
- risk assessment
- disaster response
- recovery strategies
- satellite imagery
- geospatial modeling
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