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With weather becoming more extreme both in terms of longer dry periods and more severe rain events, municipal water networks are increasingly under pressure. The effects include damages to the pipes, flash floods on the streets and combined…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-18 Felix Lorenz , Morgan Geldenhuys , Harald Sommer , Frauke Jakobs , Carsten Lüring , Volker Skwarek , Ilja Behnke , Lauritz Thamsen

To address the mounting destruction caused by floods in climate-vulnerable regions, we propose Street to Cloud, a machine learning pipeline for incorporating crowdsourced ground truth data into the segmentation of satellite imagery of…

Computer Vision and Pattern Recognition · Computer Science 2020-11-17 Veda Sunkara , Matthew Purri , Bertrand Le Saux , Jennifer Adams

Mapping the extent of flood events is a necessary and important aspect of disaster management. In recent years, deep learning methods have evolved as an effective tool to quickly label high resolution imagery and provide necessary flood…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Landon Dyken , Saugat Adhikari , Pravin Poudel , Steve Petruzza , Da Yan , Will Usher , Sidharth Kumar

Accurate precipitation estimation is critical for hydrological applications, especially in the Global South where ground-based observation networks are sparse and forecasting skill is limited. Existing satellite-based precipitation products…

Floods are large-scale natural disasters that often induce a massive number of deaths, extensive material damage, and economic turmoil. The effects are more extensive and longer-lasting in high-population and low-resource developing…

Computer Vision and Pattern Recognition · Computer Science 2022-10-11 Ahan M R , Roshan Roy , Shreyas Sunil Kulkarni , Vaibhav Soni , Ashish Chittora

The short-term prediction of precipitation is critical in many areas of life. Recently, a large body of work was devoted to forecasting radar reflectivity images. The radar images are available only in areas with ground weather radars.…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Jiří Pihrt , Rudolf Raevskiy , Petr Šimánek , Matej Choma

The shear volumes of data generated from earth observation and remote sensing technologies continue to make major impact; leaping key geospatial applications into the dual data and compute intensive era. As a consequence, this rapid…

Computer Vision and Pattern Recognition · Computer Science 2019-08-14 Dalton Lunga , Jonathan Gerrand , Hsiuhan Lexie Yang , Christopher Layton , Robert Stewart

Continuous monitoring for road flooding could be achieved through onboard computing of satellite imagery to generate near real-time insights made available to generate dynamic information for maps used for navigation. Given the existing…

Robotics · Computer Science 2024-05-07 Vishesh Vatsal , Gouranga Nandi , Primo Manilal

Seismic interpretation is now serving as a fundamental tool for depicting subsurface geology and assisting activities in various domains, such as environmental engineering and petroleum exploration. However, most of the existing…

Geophysics · Physics 2018-10-22 Haibin Di

To ensure an efficient and environmentally friendly water resource management, water management associations need means for efficient water monitoring as well as novel strategies to reduce the pollution of surface and ground water.…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-12-30 Sebastian Drost , Arne Vogt , Christian Danowski-Buhren , Simon Jirka , Verena Kirstein , Kian Pakzad , Matthes Rieke

With changing climatic conditions, we are already seeing an increase in extreme weather events and their secondary consequences, including landslides. Landslides threaten infrastructure, including roads, railways, buildings, and human life.…

Computer Vision and Pattern Recognition · Computer Science 2023-10-11 Alexandra Jarna Ganerød , Gabriele Franch , Erin Lindsay , Martina Calovi

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

When providing the boundary conditions for hydrological flood models and estimating the associated risk, interpolating precipitation at very high temporal resolutions (e.g. 5 minutes) is essential not to miss the cause of flooding in local…

Computer Vision and Pattern Recognition · Computer Science 2022-03-03 Michiaki Tatsubori , Takao Moriyama , Tatsuya Ishikawa , Paolo Fraccaro , Anne Jones , Blair Edwards , Julian Kuehnert , Sekou L. Remy

Accurate flood forecasting remains a challenge for water-resource management, as it demands modeling of local, time-varying runoff drivers (e.g., rainfall-induced peaks, baseflow trends) and complex spatial interactions across a river…

Machine Learning · Computer Science 2025-09-03 Aishwarya Sarkar , Autrin Hakimi , Xiaoqiong Chen , Hai Huang , Chaoqun Lu , Ibrahim Demir , Ali Jannesari

In this paper, the authors aim to combine the latest state of the art models in image recognition with the best publicly available satellite images to create a system for landslide risk mitigation. We focus first on landslide detection and…

Spaceborne Light Detection and Ranging (LiDAR) systems, such as NASA's Global Ecosystem Dynamics Investigation (GEDI), provide forest structure for global carbon assessments. However, geolocation uncertainties (typically 5-15 m) propagate…

Image and Video Processing · Electrical Eng. & Systems 2025-11-25 Narumasa Tsutsumida , Rei Mitsuhashi , Yoshito Sawada , Akira Kato

The Global Flood Monitoring (GFM) system of the Copernicus Emergency Management Service (CEMS) addresses the challenges and impacts that are caused by flooding. The GFM system provides global, near-real time flood extent masks for each…

Rapid identification of damaged buildings after natural disasters or on war areas is crucial to support emergency response and prioritize interventions. Earth Observation constellations provide timely, large-scale coverage, but actionable…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Thomas Goudemant , Benjamin Francesconi

Precipitation plays a critical role in the Earth's hydrological cycle, directly affecting ecosystems, agriculture, and water resource management. Accurate precipitation estimation and prediction are crucial for understanding climate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Zhenyu Yu , Hanqing Chen , Mohd Yamani Idna Idris , Pei Wang

Climate change is leading to an increase in extreme weather events, causing significant environmental damage and loss of life. Early detection of such events is essential for improving disaster response. In this work, we propose…

Computer Vision and Pattern Recognition · Computer Science 2025-06-16 Heng Fang , Hossein Azizpour
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