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Related papers: Physics-informed GANs for Coastal Flood Visualizat…

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The use of satellite imagery has become increasingly popular for disaster monitoring and response. After a disaster, it is important to prioritize rescue operations, disaster response and coordinate relief efforts. These have to be carried…

Computers and Society · Computer Science 2018-12-19 Jigar Doshi , Saikat Basu , Guan Pang

Floods are among the most common and devastating natural hazards, imposing immense costs on our society and economy due to their disastrous consequences. Recent progress in weather prediction and spaceborne flood mapping demonstrated the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Brandon Victor , Mathilde Letard , Peter Naylor , Karim Douch , Nicolas Longépé , Zhen He , Patrick Ebel

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

Wave runup is a critical factor affecting coastal flooding, shoreline changes, and damage to coastal structures. Climate change is also expected to amplify wave runup's impact on coastal areas. Therefore, fast and accurate wave runup…

Fluid Dynamics · Physics 2024-01-18 Saeed Saviz Naeini , Reda Snaiki

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…

Rapid and accurate flood extent mapping from Remote Sensing data, such as Synthetic Aperture Radar (SAR), is critical for operational disaster response, but standard Deep Learning models often produce physically impossible predictions due…

Machine Learning · Computer Science 2026-05-26 Tewodros Syum Gebre , Jagrati Talreja , Matilda Anokye , Leila Hashemi-Beni

We present Submerse, an end-to-end framework for visualizing flooding scenarios on large and immersive display ecologies. Specifically, we reconstruct a surface mesh from input flood simulation data and generate a to-scale 3D virtual scene…

Human-Computer Interaction · Computer Science 2025-01-17 Saeed Boorboor , Yoonsang Kim , Ping Hu , Josef M. Moses , Brian A. Colle , Arie E. Kaufman

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

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

Computational complexity has been the bottleneck of applying physically-based simulations on large urban areas with high spatial resolution for efficient and systematic flooding analyses and risk assessments. To address this issue of long…

Computer Vision and Pattern Recognition · Computer Science 2020-05-14 Zifeng Guo , Joao P. Leitao , Nuno E. Simoes , Vahid Moosavi

Climate hazards can cause major disasters when they occur simultaneously as compound hazards. To understand the distribution of climate risk and inform adaptation policies, scientists need to simulate a large number of physically realistic…

Machine Learning · Computer Science 2023-12-01 Alison Peard , Jim Hall

Despite continuous improvements, precipitation forecasts are still not as accurate and reliable as those of other meteorological variables. A major contributing factor to this is that several key processes affecting precipitation…

Atmospheric and Oceanic Physics · Physics 2022-11-09 Lucy Harris , Andrew T. T. McRae , Matthew Chantry , Peter D. Dueben , Tim N. Palmer

Risk communication seeks to develop a shared understanding of disaster among stakeholders, thereby amplifying public awareness and empowering them to respond more effectively to emergencies. However, existing studies have overemphasized…

Computational Engineering, Finance, and Science · Computer Science 2025-12-04 Weilian Li , Jun Zhu , Saied Pirasteh , Qing Zhu , Yukun Guo , Lan Luo , Youness Dehbi

Visualization is an essential operation when assessing the risk of rare events such as coastal or river floodings. The goal is to display a few prototype events that best represent the probability law of the observed phenomenon, a task…

Floods can cause horrific harm to life and property. However, they can be mitigated or even avoided by the effective use of hydraulic structures such as dams, gates, and pumps. By pre-releasing water via these structures in advance of…

Machine Learning · Computer Science 2023-10-31 Jimeng Shi , Vitalii Stebliankin , Giri Narasimhan

Natural disasters affect hundreds of millions of people worldwide every year. Early warning, humanitarian response and recovery mechanisms can be improved by using big data sources. Measuring the different dimensions of the impact of…

Computers and Society · Computer Science 2020-06-25 David Pastor-Escuredo , Yolanda Torres , Maria Martinez , Pedro J. Zufiria

Identification of regions affected by floods is a crucial piece of information required for better planning and management of post-disaster relief and rescue efforts. Traditionally, remote sensing images are analysed to identify the extent…

Computer Vision and Pattern Recognition · Computer Science 2022-10-05 Sushant Lenka , Pratyush Kerhalkar , Pranav Shetty , Harsh Gupta , Bhavam Vidyarthi , Ujjwal Verma

Floods cause extensive global damage annually, making effective monitoring essential. While satellite observations have proven invaluable for flood detection and tracking, comprehensive global flood datasets spanning extended time periods…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Amit Misra , Kevin White , Simone Fobi Nsutezo , William Straka , Juan Lavista

Flash floods are the most destructive natural hazard in Himachal Pradesh (HP), India, causing over 400 fatalities and $1.2 billion in losses in the 2023 monsoon season alone. Existing risk maps treat every pixel independently, ignoring the…

Machine Learning · Computer Science 2026-03-18 Paras Sharma , Swastika Sharma

Flood mapping is crucial for assessing and mitigating flood impacts, yet traditional methods like numerical modeling and aerial photography face limitations in efficiency and reliability. To address these challenges, we propose PIFF, a…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 ChunLiang Wu , Tsunhua Yang , Hungying Chen