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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

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

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

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

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

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

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

In this paper we present our methods for the MediaEval 2019 Mul-timedia Satellite Task, which is aiming to extract complementaryinformation associated with adverse events from Social Media andsatellites. For the first challenge, we propose…

Computer Vision and Pattern Recognition · Computer Science 2019-10-08 Kashif Ahmad , Konstantin Pogorelov , Mohib Ullah , Michael Riegler , Nicola Conci , Johannes Langguth , Ala Al-Fuqaha

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

This paper addresses the challenges of an early flood warning caused by complex convective systems (CSs), by using Low-Earth Orbit and Geostationary satellite data. We focus on a sequence of extreme events that took place in central Vietnam…

Image and Video Processing · Electrical Eng. & Systems 2024-09-09 Tran-Vu La , Thanh Huy Nguyen , Patrick Matgen , Marco Chini

Geospatial Artificial Intelligence (GeoAI) for satellite-based flood extent mapping systematically integrates artificial intelligence techniques with satellite data to identify flood events and assess their impacts, for disaster management…

Computer Vision and Pattern Recognition · Computer Science 2025-06-16 Hyunho Lee , Wenwen Li

In spite of astonishing advances and developments in remote sensing technologies, meeting the spatio-temporal requirements for flood hydrodynamic modeling remains a great challenge for Earth Observation. The assimilation of multi-source…

Image and Video Processing · Electrical Eng. & Systems 2024-09-09 Thanh Huy Nguyen , Sophie Ricci , Andrea Piacentini , Charlotte Emery , Raquel Rodriguez Suquet , Santiago Peña Luque

Accurate flood detection in near real time via high resolution, high latency satellite imagery is essential to prevent loss of lives by providing quick and actionable information. Instruments and sensors useful for flood detection are only…

Computer Vision and Pattern Recognition · Computer Science 2020-10-13 Peri Akiva , Matthew Purri , Kristin Dana , Beth Tellman , Tyler Anderson

Low-latency delivery of satellite imagery is essential for time-critical applications such as disaster response, intelligence, and infrastructure monitoring. However, traditional pipelines rely on downlinking all captured images before…

Machine Learning · Computer Science 2026-04-21 Ansel Kaplan Erol , Seungjun Lee , Divya Mahajan

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

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

This paper addresses the problem of floods classification and floods aftermath detection utilizing both social media and satellite imagery. Automatic detection of disasters such as floods is still a very challenging task. The focus lies on…

Information Retrieval · Computer Science 2019-01-11 Kashif Ahmad , Konstantin Pogorelov , Michael Riegler , Olga Ostroukhova , Paal Halvorsen , Nicola Conci , Rozenn Dahyot

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

The recent explosive growth of small satellite operations driven primarily from an academic or pedagogical need, has demonstrated the viability of commercial-off-the-shelf technologies in space. They have also leveraged and shown the need…

Instrumentation and Detectors · Physics 2016-07-20 André G. C. Guerra , Frederico Francisco , Jaime Villate , Fernando Aguado Agelet , Orfeu Bertolami , Kanna Rajan

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
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