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

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Nature disasters play a key role in shaping human-urban infrastructure interactions. Effective and efficient response to natural disasters is essential for building resilience and a sustainable urban environment. Two types of information…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Hao Li , Fabian Deuser , Wenping Yina , Xuanshu Luo , Paul Walther , Gengchen Mai , Wei Huang , Martin Werner

Observed records of climate extremes provide an incomplete view of risk, missing "unseen" events beyond historical experience. Ignoring spatial dependence further underestimates hazards striking multiple locations simultaneously. We…

Machine Learning · Computer Science 2026-04-10 Xinyue Liu , Xiao Peng , Shuyue Yan , Yuntian Chen , Dongxiao Zhang , Zhixiao Niu , Hui-Min Wang , Xiaogang He

Floods are an increasingly common global threat, causing emergencies and severe damage to infrastructure. During crises, organisations such as the World Food Programme use remotely sensed imagery, typically obtained through drones, for…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Vladyslav Polushko , Alexander Jenal , Jens Bongartz , Immanuel Weber , Damjan Hatic , Ronald Rösch , Thomas März , Markus Rauhut , Andreas Weinmann

Glacial Lake Outburst Floods (GLOFs) pose a serious threat in high mountain regions. They are hazardous to communities, infrastructure, and ecosystems further downstream. The classical methods of GLOF detection and prediction have so far…

Machine Learning · Computer Science 2026-01-21 Zuha Fatima , Muhammad Anser Sohaib , Muhammad Talha , Ayesha Kanwal , Sidra Sultana , Nazia Perwaiz

Floods are one of nature's most catastrophic calamities which cause irreversible and immense damage to human life, agriculture, infrastructure and socio-economic system. Several studies on flood catastrophe management and flood forecasting…

Traditional fluid dynamics simulation pipelines combine numerical solvers with rendering, producing highly realistic results but at considerable computational cost. Diffusion-based generative video models offer a faster alternative, yet…

Graphics · Computer Science 2026-03-18 Yang Bai , George Eskandar , Ziyuan Liu , Gitta Kutyniok

Gaining timely and reliable situation awareness after hazard events such as a hurricane is crucial to emergency managers and first responders. One effective way to achieve that goal is through damage assessment. Recently, disaster…

Computer Vision and Pattern Recognition · Computer Science 2020-12-17 Quoc Dung Cao , Youngjun Choe

In this paper we discuss and address the challenges of predicting extreme atmospheric events like intense rainfall, hail, and strong winds. These events can cause significant damage and have become more frequent due to climate change.…

Atmospheric and Oceanic Physics · Physics 2023-10-06 Mikhail Mozikov , Ilya Makarov , Alexandr Bulkin , Daria Taniushkina , Roland Grinis , Yury Maximov

Extreme weather events are increasingly common due to climate change, posing significant risks. To mitigate further damage, a shift towards renewable energy is imperative. Unfortunately, underrepresented communities that are most affected…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Alejandro Aparcedo , Christian Lopez , Abhinav Kotta , Mengjie Li

Forecasting global precipitation patterns and, in particular, extreme precipitation events is of critical importance to preparing for and adapting to climate change. Making accurate high-resolution precipitation forecasts using traditional…

Machine Learning · Computer Science 2022-10-25 James Duncan , Shashank Subramanian , Peter Harrington

We propose a novel approach for rapid segmentation of flooded buildings by fusing multiresolution, multisensor, and multitemporal satellite imagery in a convolutional neural network. Our model significantly expedites the generation of…

Computer Vision and Pattern Recognition · Computer Science 2018-12-06 Tim G. J. Rudner , Marc Rußwurm , Jakub Fil , Ramona Pelich , Benjamin Bischke , Veronika Kopackova , Piotr Bilinski

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

Lack of global data inventories obstructs scientific modeling of and response to landslide hazards which are oftentimes deadly and costly. To remedy this limitation, new approaches suggest solutions based on citizen science that requires…

Computer Vision and Pattern Recognition · Computer Science 2024-04-25 Ferda Ofli , Muhammad Imran , Umair Qazi , Julien Roch , Catherine Pennington , Vanessa J. Banks , Remy Bossu

Virtual flood experience systems, which enable users to vividly experience flooding, are attracting increasing attention as effective tools for communicating flood risks. However, existing systems typically rely on virtual cities that do…

Multimedia · Computer Science 2026-04-23 Tatsuro Banno , Koki Kawada , Mizuki Takenawa , Masatoshi Denda , Kiyoharu Aizawa

As Earth's climate changes, it is impacting disasters and extreme weather events across the planet. Record-breaking heat waves, drenching rainfalls, extreme wildfires, and widespread flooding during hurricanes are all becoming more frequent…

Artificial Intelligence · Computer Science 2026-05-07 Hao Li , Fabian Deuser , Wenping Yin , Steffen Knoblauch , Wufan Zhao , Filip Biljecki , Yong Xue , Wei Huang

Along with climate change, more frequent extreme events, such as flooding and tropical cyclones, threaten the livelihoods and wellbeing of poor and vulnerable populations. One of the most immediate needs of people affected by a disaster is…

Machine Learning · Computer Science 2021-08-10 Karla Saldana Ochoa , Tina Comes

Extreme precipitation events, such as violent rainfall and hail storms, routinely ravage economies and livelihoods around the developing world. Climate change further aggravates this issue. Data-driven deep learning approaches could widen…

Flooding is the most devastating phenomenon occurring globally, particularly in mountainous regions, risk dramatically increases due to complex terrains and extreme climate changes. These situations are damaging livelihoods, agriculture,…

Artificial Intelligence · Computer Science 2025-05-27 Haleema Bibi , Sadia Saleem , Zakia Jalil , Muhammad Nasir , Tahani Alsubait

The increasing impact of human-induced climate change and unplanned urban constructions has increased flooding incidents in recent years. Accurate identification of flooded areas is crucial for effective disaster management and urban…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Muhammad Umair Danish , Madhushan Buwaneswaran , Tehara Fonseka , Katarina Grolinger

With the deterioration of climate, the phenomenon of rain-induced flooding has become frequent. To mitigate its impact, recent works adopt convolutional neural network or its variants to predict the floods. However, these methods directly…

Computer Vision and Pattern Recognition · Computer Science 2023-12-13 Feifei Wang , Yong Wang , Bing Li , Qidong Huang , Shaoqing Chen