English
Related papers

Related papers: AB2CD: AI for Building Climate Damage Classificati…

200 papers

Satellite-derived data products and climate model simulations of geophysical variables like precipitation, often exhibit systematic biases compared to in-situ measurements. Bias correction and spatial downscaling are fundamental components…

Machine Learning · Computer Science 2026-02-16 Sumanta Chandra Mishra Sharma , Adway Mitra , Auroop Ratan Ganguly

Climate models (CM) are used to evaluate the impact of climate change on the risk of floods and strong precipitation events. However, these numerical simulators have difficulties representing precipitation events accurately, mainly due to…

Computational Engineering, Finance, and Science · Computer Science 2021-02-15 Rilwan Adewoyin , Peter Dueben , Peter Watson , Yulan He , Ritabrata Dutta

Interferometric Synthetic Aperture Radar (InSAR) technology uses satellite radar to detect surface deformation patterns and monitor earthquake impacts on buildings. While vital for emergency response planning, extracting multi-class…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Xuechun Li , Susu Xu

Understanding the behaviour of environmental extreme events is crucial for evaluating economic losses, assessing risks, health care and many other aspects. In the spatial context, relevant for environmental events, the dependence structure…

Methodology · Statistics 2021-03-22 Manaf Ahmed , Véronique Maume-Deschamps , Pierre Ribereau

Pavement condition evaluation is essential to time the preventative or rehabilitative actions and control distress propagation. Failing to conduct timely evaluations can lead to severe structural and financial loss of the infrastructure and…

Computer Vision and Pattern Recognition · Computer Science 2020-12-18 Sadra Naddaf-Sh , M-Mahdi Naddaf-Sh , Amir R. Kashani , Hassan Zargarzadeh

This paper presents the first AI/ML system for automating building damage assessment in uncrewed aerial systems (sUAS) imagery to be deployed operationally during federally declared disasters (Hurricanes Debby and Helene). In response to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Thomas Manzini , Priyankari Perali , Robin R. Murphy

Computational methods to accelerate natural disaster response include change detection, map alignment, and vision-aided navigation. Current software functions optimally only on near-nadir images, though off-nadir images are often the first…

Computer Vision and Pattern Recognition · Computer Science 2022-08-09 Christopher Sun , Jai Sharma , Milind Maiti

Structural damage detection is essential for maintaining the safety and reliability of civil infrastructure. However, accurately identifying different types of structural damage from images remains challenging due to variations in damage…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Saif ur Rehman Khan , Imad Ahmed Waqar , Arooj Zaib , Saad Ahmed , Sebastian Vollmer , Andreas Dengel , Muhammad Nabeel Asim

The machine learning community has recently had increased interest in the climate and disaster damage domain due to a marked increased occurrences of natural hazards (e.g., hurricanes, forest fires, floods, earthquakes). However, not enough…

Computer Vision and Pattern Recognition · Computer Science 2021-12-28 Vishal Anand , Yuki Miura

Wind turbines are subjected to continuous rotational stresses and unusual external forces such as storms, lightning, strikes by flying objects, etc., which may cause defects in turbine blades. Hence, it requires a periodical inspection to…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Md Fazle Rabbi , Solayman Hossain Emon , Ehtesham Mahmud Nishat , Tzu-Liang , Tseng , Atira Ferdoushi , Chun-Che Huang , Md Fashiar Rahman

Seismic assessment of buildings and determination of their structural damage is at the forefront of modern scientific research. Since now, several researchers have proposed a number of procedures, in an attempt to estimate the damage…

Machine Learning · Computer Science 2022-03-28 Konstantinos Demertzis , Konstantinos Kostinakis , Konstantinos Morfidis , Lazaros Iliadis

Human activities accelerate consumption of fossil fuels and produce greenhouse gases, resulting in urgent issues today: global warming and the climate change. These indirectly cause severe natural disasters, plenty of lives suffering and…

Very High Resolution (VHR) geospatial image analysis is crucial for humanitarian assistance in both natural and anthropogenic crises, as it allows to rapidly identify the most critical areas that need support. Nonetheless, manually…

Harmful algal blooms are a growing threat to inland water quality and public health worldwide, creating an urgent need for efficient, accurate, and cost-effective detection methods. This research introduces a high-performing methodology…

Machine Learning · Computer Science 2025-12-05 Ioannis Nasios

Active volcanoes are globally distributed and pose societal risks at multiple geographic scales, ranging from local hazards to regional/international disruptions. Many volcanoes do not have continuous ground monitoring networks; meaning…

Computer Vision and Pattern Recognition · Computer Science 2021-09-28 Jeremy Diaz , Guido Cervone , Christelle Wauthier

Landslides pose severe threats to infrastructure, economies, and human lives, necessitating accurate detection and predictive mapping across diverse geographic regions. With advancements in deep learning and remote sensing, automated…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Rahul A. Burange , Harsh K. Shinde , Omkar Mutyalwar

In an era of escalating climate change, urban flooding has emerged as a critical challenge for sustainable cities, threatening lives, infrastructure, and ecosystems. Traditional flood detection methods are constrained by their reliance on…

Computer Vision and Pattern Recognition · Computer Science 2025-09-11 Shahid Shafi Dar , Bharat Kaurav , Arnav Jain , Chandravardhan Singh Raghaw , Mohammad Zia Ur Rehman , Nagendra Kumar

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 utility of aerial imagery (Satellite, Drones) has become an invaluable information source for cross-disciplinary applications, especially for crisis management. Most of the mapping and tracking efforts are manual which is…

Computer Vision and Pattern Recognition · Computer Science 2020-04-28 Ruchit Rawal , Prabhu Pradhan

This document presents the Center for Robot Assisted Search And Rescue - Uncrewed Aerial Systems - Disaster Response Overhead Inspection Dataset (CRASAR-U-DROIDs) for building damage assessment and spatial alignment collected from small…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Thomas Manzini , Priyankari Perali , Raisa Karnik , Robin Murphy
‹ Prev 1 4 5 6 7 8 10 Next ›