remotesensing-logo

Journal Browser

Journal Browser

Remote Sensing of Floods: Progress, Challenges and Opportunities (Second Edition)

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 15 January 2026 | Viewed by 1977

Special Issue Editors


E-Mail Website
Guest Editor
Department of Biology, Geology and Environmental Science, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA
Interests: multispectral hyperspectral and microwave remote sensing; GIS, spatial analysis, and numerical modelling; water quality; floods; urban growth; urban heat island impact; environmental sustainability; landslides; soil moisture; climate change
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
National Center for Computational Hydroscience and Engineering, University of Mississippi, Oxford, MS 38655, USA
Interests: environmental hydraulics and computational hydraulics, with special emphasis on the modeling of hydrodynamics, water quality, chemical and oil spills, sediment transport, and environmental risk analysis for lakes, rivers, and coastal waters; integration of remote sensing with hydrodynamic models
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Harold Hamm School of Geology and Geological Engineering, University of North Dakota, Grand Forks, ND 58202, USA
Interests: remote sensing; hydrology; water quality
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Remote sensing has been used for mapping and monitoring floods for many years. Studying floods is considered one of the most common and useful applications of remote sensing. With their respective advantages and limitations, optical and microwave remote sensing techniques have been used to study floods in different parts of the world. Their advantages and limitations depend on the physiographies, land use and land cover types, and climates of the areas studied, as well as the specific characteristics of the remote sensing systems and sensors used. The recent progress in remote sensing technology, computing, and machine learning algorithms has provided tremendous opportunities to minimize the previously encountered challenges in mapping and monitoring floods. However, these advancements and topics have not been properly researched and documented. Therefore, the first volume of this Special Issue of Remote Sensing was published to present original research and review articles on the progress, challenges, and opportunities related to the remote sensing of floods. With the success of the first volume of this important Special Issue, we are excited to request more original research and review articles discussing the progress, challenges, and opportunities related to the remote sensing of floods to publish in the second volume.

Potential topics include the following:

  • Mapping, monitoring, and modeling floods using multi-sensor remote sensing methods;
  • Mapping, monitoring, and modeling floods using sensor fusion;
  • Mapping and modeling flood dynamics using remote sensing;
  • Application of SAR, LIDAR, and multispectral remote sensing for studying riverine and coastal flooding;
  • Application of remote sensing for studying flash flooding;
  • Machine learning/deep learning in the remote sensing of floods;
  • Remote sensing of floods using moderate and high-resolution imagery;
  • Remote sensing of floods using aerial/air-born/UAV imagery;
  • Integration of remote sensing with hydrodynamic models for flood simulation and prediction.

Dr. Azad Hossain
Dr. Xiaobo Chao
Dr. Taufique Mahmood
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

  • floods
  • flood monitoring
  • flood impact
  • flood damage
  • remote Sensing
  • progress, challenges, and opportunities
  • inland flooding
  • urban flooding
  • flash flooding
  • coastal flooding
  • optical remote sensing
  • RADAR remote sensing
  • hyperspectral remote sensing
  • spatial resolution
  • high/moderate/low spatial resolution
  • temporal resolution
  • high/moderate/low temporal resolution
  • space-borne remote sensing
  • air-borne remote sensing
  • drone/UAV
  • synthetic aperture radar (SAR)
  • light detection and ranging (LIDAR)
  • unmanned aerial vehicle (UAV)
  • rainfall and runoff
  • hydrology
  • geospatial technology
  • spatial analysis
  • numerical model
  • hydrodynamic model
  • spatial decision support systems (SDSS)
  • watershed model

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

29 pages, 61178 KB  
Article
Post-Hurricane Debris and Community Flood Damage Assessment Using Aerial Imagery
by Diksha Aggarwal, Suyog Gautam, Daniel Whitehurst and Kevin Kochersberger
Remote Sens. 2025, 17(18), 3171; https://doi.org/10.3390/rs17183171 - 12 Sep 2025
Viewed by 840
Abstract
Natural disasters often result in significant damage to infrastructure, generating vast amounts of debris in towns and water bodies. Timely post-disaster damage assessment is critical for enabling swift cleanup and recovery efforts. This study presents a combination of methods to efficiently estimate and [...] Read more.
Natural disasters often result in significant damage to infrastructure, generating vast amounts of debris in towns and water bodies. Timely post-disaster damage assessment is critical for enabling swift cleanup and recovery efforts. This study presents a combination of methods to efficiently estimate and analyze debris on land and on water. Specifically, analyses were conducted at Claytor Lake and Damascus, Virginia where flooding occurred as a result of Hurricane Helene on 27 September 2024. We use the Phoenix U15 motor glider equipped with the GoPro Hero 9 camera to collect aerial imagery. Orthomosaic images and 3D maps are generated using OpenDroneMap (ODM) software, version 3.5.6, providing a detailed view of the affected areas. For lake debris estimation, we employ a hybrid approach integrating machine learning-based tools and traditional techniques. Lake regions are isolated using segmentation methods, and the debris area is estimated through a combination of color thresholding and edge detection. The debris is classified based on the thickness and a volume range of debris is presented based on the data provided by the Virginia Department of Environmental Quality (VDEQ). In Damascus, debris estimation is achieved by comparing pre-disaster LiDAR data (2016) with post-disaster 3D ODM data. Furthermore, we conduct flood modeling using the Hydrologic Engineering Center’s River Analysis System (HEC-RAS) to simulate disaster impacts, estimate the flood water depth, and support urban planning efforts. The proposed methodology demonstrates the ability to deliver accurate debris estimates in a time-sensitive manner, providing valuable insights for disaster management and environmental recovery initiatives. Full article
Show Figures

Graphical abstract

Back to TopTop