Flood Monitoring, Modelling, Forecasting and Analysis with Remote Sensing Tools

Dear Colleagues,

Remote sensing technology has become an important tool to monitor natural disasters due to its advantages of large space coverage, short revisit periods, and abundant observation variables (e.g., rainfall, soil moisture, water storage, altimetry, water surface area, etc.). Floods, a natural disaster that develops rapidly and affects a wide range of areas, can also be monitored using remote sensing. The increasing availability of multi-source satellite data improves the spatiotemporal resolution of remote-sensing-based flood monitoring and presents opportunities to overcome previously encountered challenges in flood mapping. Moreover, the recent progress of machine learning algorithms also provides new ways to improve the efficiency and accuracy of remote-sensing-based flood detection. In addition to directly observing floodwater bodies, remote sensing data can be combined with hydrological and hydrodynamic models to overcome the discontinuous nature of satellite observations, create better models and forecast the dynamics of flood inundation. Additional remote sensing products, such as building footprints, night-time lights, and crop types, also play vital roles in flood impact prediction and analysis. In summary, it is of great value to further investigate the information and expand the application of remote sensing data to promote research into flood monitoring, modelling, forecasting and analysis. Therefore, this Special Issue invites papers on the following topics:

• Flood monitoring using multi-sensor remote sensing data;
• Flood monitoring algorithms based on new technologies such as machine learning;
• Flood monitoring in obstacle areas (urban, vegetated, and mountain areas, etc.) or special land cover regions (desert and snow regions, etc.) with remote sensing data;
• Calibrating and validating flood models, and data assimilation, using remote sensing data;
• Flood forecasting using remote sensing data (such as soil water, rainfall data, etc.);
• Analysis of flood hazards, risk, damages, vulnerability, resilience, etc., using remote sensing data.

Dr. Xudong Zhou
Dr. Leila Hashemi Beni
Dr. Menaka Revel
Dr. Qing Yang
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 250 words) can be sent to the Editorial Office for assessment.

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.