Dear Colleagues,

According to the World Health Organization, every year, natural disasters kill around 90,000 people and affect nearly 160 million people worldwide. Furthermore, there is an urgency to prepare for any future adversity as the frequency and magnitude of natural disasters are increasing due to urbanization, climate change, environmental issues, etc. GIS and Remote Sensing fields play a vital role in disaster management with access to various remote sensing platforms, existing maps, data processing and decision-making algorithms. With the new advancements in the fields, especially regarding machine/deep learning and 3D city modeling, it is worth thinking about how these advancements can be employed in disaster management efforts.

Based on the literature, disaster management efforts can be summarized in four stages: Preparedness, Response, Recovery and Prevention. While Geospatial data are used for all four stages, in this Special Issue, we focus on new advancements in the Response efforts, which include damage map generation and post-disaster coordination. This includes but is not limited to:

• Application of machine learning in disaster coordination;
• Utilization of Deep Neural Networks in damage map generation;
• Identification of the best feature layers and machine learning algorithms for damage map generation;
• Generation of damage map in a timely manner considering the urgency of the response efforts;
• Estimation of damage levels using multi-modal data sources;
• Utilization of existing and perhaps outdated GIS resources in disaster response;
• Estimation of damage using only post-disaster data sources.

Dr. Shabnam Jabari
Guest Editor

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.

• Disaster management
• Damage mapping
• Damage level estimation
• 3D change estimation
• Deep learning
• Machine learning
• Geospatial databases
• Disaster response
• SAR image change detection
• Optical change detection