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Satellite remote sensing is playing an increasing role in the rapid mapping of damage after natural disasters. In particular, synthetic aperture radar (SAR) can image the Earth's surface and map damage in all weather conditions, day and…

Building damage identification shortly after a disaster is crucial for guiding emergency response and recovery efforts. Although optical satellite imagery is commonly used for disaster mapping, its effectiveness is often hampered by cloud…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Luigi Russo , Deodato Tapete , Silvia Liberata Ullo , Paolo Gamba

Quick and automated earthquake-damaged building detection from post-event satellite imagery is crucial, yet it is challenging due to the scarcity of training data required to develop robust algorithms. This letter presents the first dataset…

Image and Video Processing · Electrical Eng. & Systems 2024-04-08 Yao Sun , Yi Wang , Michael Eineder

Critical infrastructure, such as transport networks and bridges, are systematically targeted during wars and suffer damage during extensive natural disasters because it is vital for enabling connectivity and transportation of people and…

When disaster strikes, accurate situational information and a fast, effective response are critical to save lives. Widely available, high resolution satellite images enable emergency responders to estimate locations, causes, and severity of…

Computer Vision and Pattern Recognition · Computer Science 2020-04-15 Hanxiang Hao , Sriram Baireddy , Emily R. Bartusiak , Latisha Konz , Kevin LaTourette , Michael Gribbons , Moses Chan , Mary L. Comer , Edward J. Delp

Natural disasters ravage the world's cities, valleys, and shores on a regular basis. Deploying precise and efficient computational mechanisms for assessing infrastructure damage is essential to channel resources and minimize the loss of…

Computer Vision and Pattern Recognition · Computer Science 2022-01-28 Thomas Y. Chen

Accurate assessment of post-disaster damage is essential for prioritizing emergency response, yet current practices rely heavily on manual interpretation of satellite imagery.This approach is time-consuming, subjective, and difficult to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Sreesritha Sai , Sai Venkata Suma Sreeja , Sai Sri Deepthi , Nikhil

Satellite imagery has played an increasingly important role in post-disaster building damage assessment. Unfortunately, current methods still rely on manual visual interpretation, which is often time-consuming and can cause very low…

Computer Vision and Pattern Recognition · Computer Science 2024-05-09 Irene Alisjahbana , Jiawei Li , Ben , Strong , Yue Zhang

Timely and accurate assessments of building damage are crucial for effective response and recovery in the aftermath of earthquakes. Conventional preliminary damage assessments (PDA) often rely on manual door-to-door inspections, which are…

Computer Vision and Pattern Recognition · Computer Science 2025-06-19 Deepank Singh , Vedhus Hoskere , Pietro Milillo

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

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

This paper presents \dahitra, a novel deep-learning model with hierarchical transformers to classify building damages based on satellite images in the aftermath of natural disasters. Satellite imagery provides real-time and high-coverage…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Navjot Kaur , Cheng-Chun Lee , Ali Mostafavi , Ali Mahdavi-Amiri

Multimedia content in social media platforms provides significant information during disaster events. The types of information shared include reports of injured or deceased people, infrastructure damage, and missing or found people, among…

Computer Vision and Pattern Recognition · Computer Science 2020-04-27 Ferda Ofli , Firoj Alam , Muhammad Imran

High-resolution satellite imagery available immediately after disaster events is crucial for response planning as it facilitates broad situational awareness of critical infrastructure status such as building damage, flooding, and…

Computer Vision and Pattern Recognition · Computer Science 2021-11-09 Danil Kuzin , Olga Isupova , Brooke D. Simmons , Steven Reece

Satellite images are an extremely valuable resource in the aftermath of natural disasters such as hurricanes and tsunamis where they can be used for risk assessment and disaster management. In order to provide timely and actionable…

Image and Video Processing · Electrical Eng. & Systems 2020-06-11 Ananya Gupta , Simon Watson , Hujun Yin

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

Disaster events occur around the world and cause significant damage to human life and property. Earth observation (EO) data enables rapid and comprehensive building damage assessment (BDA), an essential capability in the aftermath of a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Hongruixuan Chen , Jian Song , Olivier Dietrich , Clifford Broni-Bediako , Weihao Xuan , Junjue Wang , Xinlei Shao , Yimin Wei , Junshi Xia , Cuiling Lan , Konrad Schindler , Naoto Yokoya

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 all types of disasters, from earthquakes to armed conflicts, aid workers need accurate and timely data such as damage to buildings and population displacement to mount an effective response. Remote sensing provides this data at an…

Computer Vision and Pattern Recognition · Computer Science 2019-10-16 Joseph Z. Xu , Wenhan Lu , Zebo Li , Pranav Khaitan , Valeriya Zaytseva

Accurate and fine-grained information about the extent of damage to buildings is essential for directing Humanitarian Aid and Disaster Response (HADR) operations in the immediate aftermath of any natural calamity. In recent years, satellite…

Computer Vision and Pattern Recognition · Computer Science 2020-04-17 Rohit Gupta , Mubarak Shah
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