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Satellites equipped with optical sensors capture high-resolution imagery, providing valuable insights into various environmental phenomena. In recent years, there has been a surge of research focused on addressing some challenges in remote…

Computer Vision and Pattern Recognition · Computer Science 2024-03-04 Loddo Fabio , Dario Piga , Michelucci Umberto , El Ghazouali Safouane

Accurate precipitation estimation is critical for flood forecasting, water resource management, and disaster preparedness. Satellite products provide global hourly coverage but contain systematic biases; ground-based gauges are accurate at…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Shunya Nagashima , Takumi Bannai , Shuitsu Koyama , Tomoya Mitsui , Shuntaro Suzuki

Earth Observation imagery can capture rare and unusual events, such as disasters and major landscape changes, whose visual appearance contrasts with the usual observations. Deep models trained on common remote sensing data will output…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Georges Le Bellier , Nicolas Audebert

Understanding flood probabilities is essential to making sound decisions about flood-risk management. Many people rely on flood probability maps to inform decisions about purchasing flood insurance, buying or selling real-estate,…

Applications · Statistics 2020-12-22 Mahkameh Zarekarizi , K. Joel Roop-Eckart , Sanjib Sharma , Klaus Keller

Gridded satellite precipitation datasets are useful in hydrological applications as they cover large regions with high density. However, they are not accurate in the sense that they do not agree with ground-based measurements. An…

Atmospheric and Oceanic Physics · Physics 2023-03-06 Georgia Papacharalampous , Hristos Tyralis , Anastasios Doulamis , Nikolaos Doulamis

Recent advancements in computer vision and deep learning techniques have facilitated notable progress in scene understanding, thereby assisting rescue teams in achieving precise damage assessment. In this paper, we present RescueNet, a…

Computer Vision and Pattern Recognition · Computer Science 2024-05-20 Maryam Rahnemoonfar , Tashnim Chowdhury , Robin Murphy

Human civilization has an increasingly powerful influence on the earth system. Affected by climate change and land-use change, natural disasters such as flooding have been increasing in recent years. Earth observations are an invaluable…

Computer Vision and Pattern Recognition · Computer Science 2022-12-08 Ritu Yadav , Andrea Nascetti , Hossein Azizpour , Yifang Ban

Most post-disaster damage classifiers succeed only when destructive forces leave clear spectral or structural signatures -- conditions rarely present after inundation. Consequently, existing models perform poorly at identifying…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Yu-Hsuan Ho , Ali Mostafavi

Applications such as web search and social networking have been moving from centralized to decentralized cloud architectures to improve their scalability. MapReduce, a programming framework for processing large amounts of data using…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-24 Pedro A. R. S. Costa , Xiao Bai , Fernando M. V. Ramos , Miguel Correia

High energy solar flares and coronal mass ejections have the potential to destroy Earth's ground and satellite infrastructures, causing trillions of dollars in damage and mass human suffering. Destruction of these critical systems would…

Machine Learning · Computer Science 2021-10-18 Erik Larsen

Climate change and increasing droughts pose significant challenges to water resource management around the world. These problems lead to severe water shortages that threaten ecosystems, agriculture, and human communities. To advance the…

Image and Video Processing · Electrical Eng. & Systems 2024-10-22 Luigi Russo , Francesco Mauro , Alessandro Sebastianelli , Paolo Gamba , Silvia Liberata Ullo

Mapping land surface disturbances supports disaster response, resource and ecosystem management, and climate adaptation efforts. Synthetic aperture radar (SAR) is an invaluable tool for disturbance mapping, providing consistent time-series…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Harris Hardiman-Mostow , Charles Marshak , Alexander L. Handwerger

In recent years, there has been a growing demand for improved autonomy for in-orbit operations such as rendezvous, docking, and proximity maneuvers, leading to increased interest in employing Deep Learning-based Spacecraft Pose Estimation…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Arunkumar Rathinam , Haytam Qadadri , Djamila Aouada

The accumulated remote sensing data of altimeters and scatterometers have provided a new opportunity to forecast the ocean states and improve the knowledge in ocean/atmosphere exchanges. Few previous studies have focused on sea level…

Atmospheric and Oceanic Physics · Physics 2020-06-16 Guosong Wang , Xidong Wang , Xinrong Wu , Kexiu Liu , Yiquan Qi , Chunjian Sun , Hongli Fu

Accurate change detection from satellite imagery is essential for monitoring rapid mass-movement hazards such as snow avalanches, which increasingly threaten human life, infrastructure, and ecosystems due to their rising frequency and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Mattia Gatti , Alberto Mariani , Ignazio Gallo , Fabiano Monti

This paper argues that AI-enabled analysis of street-view imagery, complemented by performance-gated machine-learning imputation, provides a viable pathway for generating building-specific elevation data at regional scale for flood risk…

Machine Learning · Computer Science 2026-04-03 Xiangpeng Li , Yu-Hsuan Ho , Sam D Brody , Ali Mostafavi

Understanding the extent of urban flooding is crucial for assessing building damage, casualties and economic losses. Synthetic Aperture Radar (SAR) technology offers significant advantages for mapping flooded urban areas due to its ability…

Image and Video Processing · Electrical Eng. & Systems 2024-11-08 Jie Zhao , Ming Li , Yu Li , Patrick Matgen , Marco Chini

Predicting flood for any location at times of extreme storms is a longstanding problem that has utmost importance in emergency management. Conventional methods that aim to predict water levels in streams use advanced hydrological models…

Machine Learning · Computer Science 2019-06-25 Muhammed Sit , Ibrahim Demir

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

In recent years, landslide disasters have reported frequently due to the extreme weather events of droughts, floods , storms, or the consequence of human activities such as deforestation, excessive exploitation of natural resources.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-16 Lam Pham , Cam Le , Hieu Tang , Khang Truong , Truong Nguyen , Jasmin Lampert , Alexander Schindler , Martin Boyer , Son Phan