Dear Colleagues,

The combination of remote sensing, physics-based numerical simulation, and advanced machine learning technologies is instrumental in understanding several aspects of the Earth's ever-changing surface. Mainly, disaster science research has seen considerable attention, yielding novel methodologies for rapid post-disaster damage assessments and an accurate understanding of hazard scenarios before disasters. On the one hand, integrating numerical modeling and machine learning technologies allows us to analyze several Earth phenomena, such as ground deformations, growing urban environments, and local-site characterization. Furthermore, earth observation technologies, such as optical imaging and radar-based sensing, can capture changes before and after disasters. However, complex and unique disaster conditions induced by earthquakes, heavy rain, and other natural phenomena present significant challenges due to several factors, such as data accessibility, missing information, and high computation cost. Thus, this Special Issue explores the theory and combined application of numerical modeling, machine learning, and remote sensing technologies for disaster damage and loss assessments.

This Special Issue is open to all contributions on recent advances and novel developments of methodologies and best-case study application of computer simulation, remote sensing, and machine to earthquakes, tsunamis, volcanic, and flooding events. We encourage submissions of both review and original research articles related, but not limited, to the following topics:

• Analysis of changes in urban environment;
• Damage recognition and mapping;
• Machine learning for disaster research;
• Detection and classification of building damage;
• Extraction and mapping of flooded areas;
• Time-series analysis of surface deformations;
• Open data and big data for multi-hazard analysis;
• Natural hazard modeling and prediction.

Dr. Bruno Adriano
Dr. Erick Mas
Dr. Luis Angel Moya Huallpa
Dr. Hiroyuki Miura
Prof. Dr. Miguel Estrada
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.

• earthquake damage
• tsunami events
• flood damage
• loss estimation
• optical imaging
• synthetic aperture radar
• machine learning