English
Related papers

Related papers: Standardized Analysis Ready (STAR) data cube for h…

200 papers

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

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

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

Floods wreak havoc throughout the world, causing billions of dollars in damages, and uprooting communities, ecosystems and economies. The NASA Impact Flood Detection competition tasked participants with predicting flooded pixels after…

Computer Vision and Pattern Recognition · Computer Science 2021-10-26 Sayak Paul , Siddha Ganju

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

Relevant comprehension of flood hazards has emerged as a crucial necessity, especially as the severity and the occurrence of flood events intensify with climate changes. Flood simulation and forecast capability have been greatly improved…

Image and Video Processing · Electrical Eng. & Systems 2022-11-18 Thanh Huy Nguyen , Anthéa Delmotte , Christophe Fatras , Peter Kettig , Andrea Piacentini , Sophie Ricci

With the escalating frequency of floods posing persistent threats to human life and property, satellite remote sensing has emerged as an indispensable tool for monitoring flood hazards. SpaceNet8 offers a unique opportunity to leverage…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Yanbing Bai , Zihao Yang , Jinze Yu , Rui-Yang Ju , Bin Yang , Erick Mas , Shunichi Koshimura

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

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

In this study, Synthetic Aperture Radar (SAR) and optical data are both considered for Earth surface classification. Specifically, the integration of Sentinel-1 (S-1) and Sentinel-2 (S-2) data is carried out through supervised Machine…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Francesca Razzano , Mariapia Rita Iandolo , Chiara Zarro , G. S. Yogesh , Silvia Liberata Ullo

Change detection using earth observation data plays a vital role in quantifying the impact of disasters in affected areas. While data sources like Sentinel-2 provide rich optical information, they are often hindered by cloud cover, limiting…

Computer Vision and Pattern Recognition · Computer Science 2023-06-16 Ritu Yadav , Andrea Nascetti , Yifang Ban

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

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

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…

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

Due to climate and land-use change, natural disasters such as flooding have been increasing in recent years. Timely and reliable flood detection and mapping can help emergency response and disaster management. In this work, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2022-12-13 Ritu Yadav , Andrea Nascetti , Yifang Ban

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

Floods are increasingly frequent natural disasters causing extensive human and economic damage, highlighting the critical need for rapid and accurate flood inundation mapping. While remote sensing technologies have advanced flood monitoring…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Tomohiro Tanaka , Narumasa Tsutsumida

A reliable yet inexpensive tool for the estimation of flood water spread is conducive for efficient disaster management. The application of optical and SAR imagery in tandem provides a means of extended availability and enhanced reliability…

Computer Vision and Pattern Recognition · Computer Science 2023-06-12 Usman Nazir , Muhammad Ahmad Waseem , Falak Sher Khan , Rabia Saeed , Syed Muhammad Hasan , Momin Uppal , Zubair Khalid
‹ Prev 1 2 3 10 Next ›