Remote Sensing of Urban Disaster Monitoring and Reduction
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: closed (25 January 2024) | Viewed by 3796
Special Issue Editors
Interests: machine learning; classification; remote sensing
Interests: high-performance geo-computation; big earth data; data science
Special Issues, Collections and Topics in MDPI journals
2. Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou 310058, China
Interests: spatio-temporal modeling; high-performance geocomputing; environmental geography
Interests: hydrogeology; geomorphology; natural hazards; land use/cover changes; optical/radar remote sensing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Climate-change-induced population shifts and economic growth are both contributing to a rise in the number of people living in areas vulnerable to natural disasters such as earthquakes and tsunamis. This Special Issue will cover all aspects of natural disasters that affect urban areas. Among the most prevalent natural disasters that can affect cities are volcanic eruptions, earthquakes, flooding, and climate-forcing extreme occurrences. Moreover, we would like to incorporate case studies of recent disasters that have affected urban areas and the response of local governments.
Growing access to Earth Observation geospatial data and the rapid development of AI technology have facilitated the use of remote sensing in urban disaster monitoring and reduction. In this Special Issue, we will focus on the impacts of urban disasters on urban areas using remote sensing data. We wish to showcase research papers, case studies, conceptual or analytic reviews, and policy-relevant articles with the aim to help minimize the impacts of urban disasters and their reductions. Topics of interest include, but are not limited to:
- The development of the new capture methods of remote sensing data on urban disasters such as floods, tsunamis, landslides, etc.;
- Muti-modal/temporal urban disaster monitoring;
- Urban disaster monitoring by integrating remote-sensed images and social media data;
- Hazards, vulnerability, recovery, and risk of urban disasters;
- Urban disaster condition monitoring and loss assessment;
- Urban disaster mitigation and adaptation;
- Applications in natural disasters in urban areas;
- Applications in natural disaster reduction.
Dr. Junshi Xia
Prof. Dr. Guoqing Li
Dr. Feng Zhang
Dr. Magaly Koch
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
- urban disaster
- monitoring and reduction
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