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Due to its cloud-penetrating capability and independence from solar illumination, satellite Synthetic Aperture Radar (SAR) is the preferred data source for large-scale flood mapping, providing global coverage and including various land…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Jie Zhao , Zhitong Xiong , Xiao Xiang Zhu

Satellite remote sensing presents a cost-effective solution for synoptic flood monitoring, and satellite-derived flood maps provide a computationally efficient alternative to numerical flood inundation models traditionally used. While…

Geophysics · Physics 2022-09-05 Antara Dasgupta , Lasse Hybbeneth , Björn Waske

This study introduces a novel dataset for segmenting flooded areas in satellite images. After reviewing 77 existing benchmarks utilizing satellite imagery, we identified a shortage of suitable datasets for this specific task. To fill this…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Youngsun Jang , Dongyoun Kim , Chulwoo Pack , Kwanghee Won

Flooding is one of the most destructive natural hazards worldwide, posing serious risks to ecosystems, infrastructure, and human livelihoods. This study combines Synthetic Aperture Radar (SAR) imagery with environmental and hydrological…

Machine Learning · Computer Science 2025-12-29 Edwin Oluoch Awino , Denis Machanda

Global floods, exacerbated by climate change, pose severe threats to human life, infrastructure, and the environment. Recent catastrophic events in Pakistan and New Zealand underscore the urgent need for precise flood mapping to guide…

Identifying flood affected areas in remote sensing data is a critical problem in earth observation to analyze flood impact and drive responses. While a number of methods have been proposed in the literature, there are two main limitations…

Computer Vision and Pattern Recognition · Computer Science 2024-03-07 Xavier Bou , Thibaud Ehret , Rafael Grompone von Gioi , Jeremy Anger

Accurate detection of inundated water extents during flooding events is crucial in emergency response decisions and aids in recovery efforts. Satellite Remote Sensing data provides a global framework for detecting flooding extents.…

Computer Vision and Pattern Recognition · Computer Science 2023-11-17 Muthukumaran Ramasubramanian , Iksha Gurung , Shubhankar Gahlot , Ronny Hänsch , Andrew L. Molthan , Manil Maskey

Climate change has increased the severity and frequency of weather disasters all around the world. Flood inundation mapping based on earth observation data can help in this context, by providing cheap and accurate maps depicting the area…

Machine Learning · Computer Science 2023-03-02 Kevin Iselborn , Marco Stricker , Takashi Miyamoto , Marlon Nuske , Andreas Dengel

Floods are one of the most common disasters globally. Flood affects humans in many ways. Therefore, rapid assessment is needed to assess the effect of floods and to take early action to support the vulnerable community in time. Sentinel-1…

Computers and Society · Computer Science 2023-11-28 Surajit Ghosh , Arpan Dawn , Sneha Kour , Susmita Ghosh

Accurate flood detection from visual data is a critical step toward improving disaster response and risk assessment, yet datasets for flood segmentation remain scarce due to the challenges of collecting and annotating large-scale imagery.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Georgios Simantiris , Konstantinos Bacharidis , Apostolos Papanikolaou , Petros Giannakakis , Costas Panagiotakis

Current Synthetic Aperture Radar (SAR)-based flood detection methods face critical limitations that hinder operational deployment. Supervised learning approaches require extensive labeled training data, exhibit poor geographical…

Applications · Statistics 2025-10-15 Narumasa Tsutsumida , Tomohiro Tanaka , Nifat Sultana

Mapping floods using satellite data is crucial for managing and mitigating flood risks. Satellite imagery enables rapid and accurate analysis of large areas, providing critical information for emergency response and disaster management.…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Jonathan Giezendanner , Rohit Mukherjee , Matthew Purri , Mitchell Thomas , Max Mauerman , A. K. M. Saiful Islam , Beth Tellman

Understanding the extent of urban flooding is crucial for assessing building damage, casualties and economic losses. Synthetic Aperture Radar (SAR) technology offers significant advantages for mapping flooded urban areas due to its ability…

Image and Video Processing · Electrical Eng. & Systems 2024-11-08 Jie Zhao , Ming Li , Yu Li , Patrick Matgen , Marco Chini

Floods are among the most damaging weather-related hazards, and in 2024, the warmest year on record, extreme flood events affected communities across five continents. Earth observation (EO) satellites provide critical, frequent coverage for…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Mirela G. Tulbure , Julio Caineta , Mark Broich , Mollie D. Gaines , Philippe Rufin , Leon-Friedrich Thomas , Hamed Alemohammad , Jan Hemmerling , Patrick Hostert

Driven by rapid climate change, the frequency and intensity of flood events are increasing. Electro-Optical (EO) satellite imagery is commonly utilized for rapid response. However, its utilities in flood situations are hampered by issues…

Computer Vision and Pattern Recognition · Computer Science 2023-07-17 Minseok Seo , Youngtack Oh , Doyi Kim , Dongmin Kang , Yeji Choi

Floods are one of the most common natural disasters, with a disproportionate impact in developing countries that often lack dense streamflow gauge networks. Accurate and timely warnings are critical for mitigating flood risks, but…

Flooding is one of the most destructive and costly natural disasters, and climate changes would further increase risks globally. This work presents a novel multimodal machine learning approach for multi-year global flood risk prediction,…

Machine Learning · Computer Science 2023-01-31 Cynthia Zeng , Dimitris Bertsimas

The detection of flooded areas using high-resolution synthetic aperture radar (SAR) imagery is a critical task with applications in crisis and disaster management, as well as environmental resource planning. However, the complex nature of…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Tamer Saleh , Xingxing Weng , Shimaa Holail , Chen Hao , Gui-Song Xia

Satellite imaging is a critical technology for monitoring and responding to natural disasters such as flooding. Despite the capabilities of modern satellites, there is still much to be desired from the perspective of first response…

Image and Video Processing · Electrical Eng. & Systems 2020-01-17 Gonzalo Mateo-Garcia , Silviu Oprea , Lewis Smith , Josh Veitch-Michaelis , Guy Schumann , Yarin Gal , Atılım Güneş Baydin , Dietmar Backes

Flooding remains a major global challenge, worsened by climate change and urbanization, demanding advanced solutions for effective disaster management. While traditional 2D flood mapping techniques provide limited insights, 3D flood…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Wenfeng Jia , Bin Liang , Yuxi Liu , Muhammad Arif Khan , Lihong Zheng
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