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We present xBD, a new, large-scale dataset for the advancement of change detection and building damage assessment for humanitarian assistance and disaster recovery research. Natural disaster response requires an accurate understanding of…

Computer Vision and Pattern Recognition · Computer Science 2019-11-22 Ritwik Gupta , Richard Hosfelt , Sandra Sajeev , Nirav Patel , Bryce Goodman , Jigar Doshi , Eric Heim , Howie Choset , Matthew Gaston

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

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

Accurately assessing building damage is critical for disaster response and recovery. However, many existing models for detecting building damage have poor prediction accuracy due to their limited capabilities of identifying detailed,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Zhuoqun Xue , Xiaojian Zhang , David O. Prevatt , Jennifer Bridge , Susu Xu , Xilei Zhao

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

Post-disaster assessments of buildings and infrastructure are crucial for both immediate recovery efforts and long-term resilience planning. This research introduces an innovative approach to automating post-disaster assessments through…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Robinson Umeike , Thang Dao , Shane Crawford

Rapid and accurate post-hurricane damage assessment is vital for disaster response and recovery. Yet existing CNN-based methods struggle to capture multi-scale spatial features and to distinguish visually similar or co-occurring damage…

Computer Vision and Pattern Recognition · Computer Science 2025-09-08 Zhangding Liu , Neda Mohammadi , John E. Taylor

Following an earthquake, it is vital to quickly evaluate the safety of the impacted areas. Damage detection systems, powered by computer vision and deep learning, can assist experts in this endeavor. However, the lack of extensive, labeled…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Piercarlo Dondi , Alessio Gullotti , Michele Inchingolo , Ilaria Senaldi , Chiara Casarotti , Luca Lombardi , Marco Piastra

In the aftermath of an earthquake, rapid structural inspections are required to get citizens back in to their homes and offices in a safe and timely manner. These inspections gfare typically conducted by municipal authorities through…

Computer Vision and Pattern Recognition · Computer Science 2018-09-26 Vedhus Hoskere , Yasutaka Narazaki , Tu A. Hoang , Billie F. Spencer

Post-disaster inspections are critical to emergency management after earthquakes. The availability of data on the condition of civil infrastructure immediately after an earthquake is of great importance for emergency management.…

Signal Processing · Electrical Eng. & Systems 2020-09-25 Xiao Liang , Seyed Omid Sajedi

Fast and effective responses are required when a natural disaster (e.g., earthquake, hurricane, etc.) strikes. Building damage assessment from satellite imagery is critical before relief effort is deployed. With a pair of pre- and…

Computer Vision and Pattern Recognition · Computer Science 2022-02-16 Yu Shen , Sijie Zhu , Taojiannan Yang , Chen Chen , Delu Pan , Jianyu Chen , Liang Xiao , Qian Du

The detrimental impacts of climate change include stronger and more destructive hurricanes happening all over the world. Identifying different damaged structures of an area including buildings and roads are vital since it helps the rescue…

Computer Vision and Pattern Recognition · Computer Science 2021-06-03 Tashnim Chowdhury , Maryam Rahnemoonfar

The use of satellite imagery has become increasingly popular for disaster monitoring and response. After a disaster, it is important to prioritize rescue operations, disaster response and coordinate relief efforts. These have to be carried…

Computers and Society · Computer Science 2018-12-19 Jigar Doshi , Saikat Basu , Guan Pang

Natural disasters demand rapid damage assessment to guide humanitarian response. Here, we investigate whether medium-resolution Earth observation images from the Copernicus program can support building damage assessment, complementing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Olivier Dietrich , Merlin Alfredsson , Emilia Arens , Nando Metzger , Torben Peters , Linus Scheibenreif , Jan Dirk Wegner , Konrad Schindler

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

In the United States, hurricanes are the most devastating natural disasters causing billions of dollars worth of damage every year. More importantly, construction jobsites are classified among the most vulnerable environments to severe wind…

Computer Vision and Pattern Recognition · Computer Science 2021-10-26 Mirsalar Kamari , Youngjib Ham

Fast and effective responses are required when a natural disaster (e.g., earthquake, hurricane, etc.) strikes. Building damage assessment from satellite imagery is critical before an effective response is conducted. High-resolution…

Computer Vision and Pattern Recognition · Computer Science 2020-11-20 Yu Shen , Sijie Zhu , Taojiannan Yang , Chen Chen

In the field of post-disaster assessment, for timely and accurate rescue and localization after a disaster, people need to know the location of damaged buildings. In deep learning, some scholars have proposed methods to make automatic and…

Computer Vision and Pattern Recognition · Computer Science 2022-06-30 Zaishuo Xia , Zelin Li , Yanbing Bai , Jinze Yu , Bruno Adriano

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

Street-view images offer unique advantages for disaster damage estimation as they capture impacts from a visual perspective and provide detailed, on-the-ground insights. Despite several investigations attempting to analyze street-view…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Yifan Yang , Lei Zou , Bing Zhou , Daoyang Li , Binbin Lin , Joynal Abedin , Mingzheng Yang