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This study aims to enable more reliable automated post-disaster building damage classification using artificial intelligence (AI) and multi-view imagery. The current practices and research efforts in adopting AI for post-disaster damage…

Computer Vision and Pattern Recognition · Computer Science 2022-08-26 Asim Bashir Khajwal , Chih-Shen Cheng , Arash Noshadravan

Classification of the extent of damage suffered by a building in a seismic event is crucial from the safety perspective and repairing work. In this study, authors have proposed a CNN based autonomous damage detection model. Over 1200 images…

Computer Vision and Pattern Recognition · Computer Science 2019-07-19 Dhananjay Nahata , Harish Kumar Mulchandani , Suraj Bansal , G Muthukumar

Rapid and accurate structural damage assessment following natural disasters is critical for effective emergency response and recovery. However, remote sensing imagery often suffers from low spatial resolution, contextual ambiguity, and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Bijay Shakya , Catherine Hoier , Khandaker Mamun Ahmed

Natural disasters pose significant challenges to timely and accurate damage assessment due to their sudden onset and the extensive areas they affect. Traditional assessment methods are often labor-intensive, costly, and hazardous to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Catherine Hoier , Khandaker Mamun Ahmed

Developing a rapid, but also reliable and efficient, method for classifying the seismic damage potential of buildings constructed in countries with regions of high seismicity is always at the forefront of modern scientific research. Such a…

Machine Learning · Computer Science 2022-05-03 Konstantinos Kostinakis , Konstantinos Morfidis , Konstantinos Demertzis , Lazaros Iliadis

Building change detection is essential for monitoring urbanization, disaster assessment, urban planning and frequently updating the maps. 3D structure information from airborne light detection and ranging (LiDAR) is very effective for…

Computer Vision and Pattern Recognition · Computer Science 2022-04-28 Ritu Yadav , Andrea Nascetti , Yifang Ban

Current methods of practice for inspection of civil infrastructure typically involve visual assessments conducted manually by trained inspectors. For post-earthquake structural inspections, the number of structures to be inspected often far…

Computer Vision and Pattern Recognition · Computer Science 2018-05-04 Vedhus Hoskere , Yasutaka Narazaki , Tu Hoang , BillieF Spencer

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

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

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

In this paper, we provide two case studies to demonstrate how artificial intelligence can empower civil engineering. In the first case, a machine learning-assisted framework, BRAILS, is proposed for city-scale building information modeling.…

Computer Vision and Pattern Recognition · Computer Science 2020-08-25 Qian Yu , Chaofeng Wang , Barbaros Cetiner , Stella X. Yu , Frank Mckenna , Ertugrul Taciroglu , Kincho H. Law

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

Buildings classification using satellite images is becoming more important for several applications such as damage assessment, resource allocation, and population estimation. We focus, in this work, on buildings damage assessment (BDA) and…

Computer Vision and Pattern Recognition · Computer Science 2021-11-30 Mohammad Dimassi , Abed Ellatif Samhat , Mohammad Zaraket , Jamal Haidar , Mustafa Shukor , Ali J. Ghandour

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

Rapid, accurate, and descriptive building damage assessment is critical for directing post-disaster resources, yet current automated methods typically provide only binary (damaged/undamaged) or ordinal severity scales. This paper introduces…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Yiming Xiao , Ali Mostafavi

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

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

After a hurricane, damage assessment is critical to emergency managers for efficient response and resource allocation. One way to gauge the damage extent is to quantify the number of flooded/damaged buildings, which is traditionally done by…

Computer Vision and Pattern Recognition · Computer Science 2020-07-09 Quoc Dung Cao , Youngjun Choe

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

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
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