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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

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

Detecting changes on the Earth, such as urban development, deforestation, or natural disaster, is one of the research fields that is attracting a great deal of attention. One promising tool to solve these problems is satellite imagery.…

Computer Vision and Pattern Recognition · Computer Science 2022-03-03 Waku Hatakeyama , Shirou Kawakita , Ryohei Izawa , Masanari Kimura

Unmanned Aerial Vehicle (UAV) based remote sensing system incorporated with computer vision has demonstrated potential for assisting building construction and in disaster management like damage assessment during earthquakes. The…

Assessing the impact of a disaster in terms of asset losses and human casualties is essential for preparing effective response plans. Traditional methods include offline assessments conducted on the ground, where volunteers and first…

Machine Learning · Computer Science 2025-09-16 Saketh Vishnubhatla , Ujun Jeong , Bohan Jiang , Paras Sheth , Zhen Tan , Adrienne Raglin , Huan Liu

The usage of Unmanned Aerial Vehicles (UAVs) in the context of structural health inspection is recently gaining tremendous popularity. Camera mounted UAVs enable the fast acquisition of a large number of images often used for mapping, 3D…

Computer Vision and Pattern Recognition · Computer Science 2021-10-12 Alon Oring

Traditional disaster analysis and modelling tools for assessing the severity of a disaster are predictive in nature. Based on the past observational data, these tools prescribe how the current input state (e.g., environmental conditions,…

Machine Learning · Computer Science 2025-09-16 Saketh Vishnubhatla , Alimohammad Beigi , Rui Heng Foo , Umang Goel , Ujun Jeong , Bohan Jiang , Adrienne Raglin , Huan Liu

We introduce WarNav, a novel real-world dataset constructed from images of the open-source DATTALION repository, specifically tailored to enable the development and benchmarking of semantic segmentation models for autonomous ground vehicle…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Marc-Emmanuel Coupvent des Graviers , Hejer Ammar , Christophe Guettier , Yann Dumortier , Romaric Audigier

Monitoring and managing Earth's forests in an informed manner is an important requirement for addressing challenges like biodiversity loss and climate change. While traditional in situ or aerial campaigns for forest assessments provide…

Computer Vision and Pattern Recognition · Computer Science 2022-12-13 Alexander Becker , Stefania Russo , Stefano Puliti , Nico Lang , Konrad Schindler , Jan Dirk Wegner

In search and rescue missions, time is an important factor; fast navigation and quickly acquiring situation awareness might be matters of life and death. Hence, the use of robots in such scenarios has been restricted by the time needed to…

Robotics · Computer Science 2020-07-10 Malcolm Mielle , Martin Magnusson , Henrik Andreasson , Achim J. Lilienthal

Drones are being used to assess the situation in various disasters. In this study, we investigate a method to automatically estimate the damage status of people based on their actions in aerial drone images in order to understand disaster…

Computer Vision and Pattern Recognition · Computer Science 2023-08-10 Tomoki Arai , Kenji Iwata , Kensho Hara , Yutaka Satoh

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

Gaining timely and reliable situation awareness after hazard events such as a hurricane is crucial to emergency managers and first responders. One effective way to achieve that goal is through damage assessment. Recently, disaster…

Computer Vision and Pattern Recognition · Computer Science 2020-12-17 Quoc Dung Cao , Youngjun Choe

In the aftermath of earthquakes, social media images have become a crucial resource for disaster reconnaissance, providing immediate insights into the extent of damage. Traditional approaches to damage severity assessment in post-earthquake…

Computer Vision and Pattern Recognition · Computer Science 2025-07-04 Danrong Zhang , Huili Huang , N. Simrill Smith , Nimisha Roy , J. David Frost

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

Many municipalities and road authorities seek to implement automated evaluation of road damage. However, they often lack technology, know-how, and funds to afford state-of-the-art equipment for data collection and analysis of road damages.…

Computer Vision and Pattern Recognition · Computer Science 2020-09-01 Deeksha Arya , Hiroya Maeda , Sanjay Kumar Ghosh , Durga Toshniwal , Alexander Mraz , Takehiro Kashiyama , Yoshihide Sekimoto

Rapid and accurate building damage assessments from high-resolution satellite imagery following a natural disaster is essential to inform and optimize first responder efforts. However, performing such building damage assessments in an…

Computer Vision and Pattern Recognition · Computer Science 2023-08-28 Caleb Robinson , Simone Fobi Nsutezo , Anthony Ortiz , Tina Sederholm , Rahul Dodhia , Cameron Birge , Kasie Richards , Kris Pitcher , Paulo Duarte , Juan M. Lavista Ferres

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

Massive amounts of satellite data have been gathered over time, holding the potential to unveil a spatiotemporal chronicle of the surface of Earth. These data allow scientists to investigate various important issues, such as land use…

Computer Vision and Pattern Recognition · Computer Science 2019-12-12 Stefan Oehmcke , Christoffer Thrysøe , Andreas Borgstad , Marcos Antonio Vaz Salles , Martin Brandt , Fabian Gieseke

Automatic damage assessment based on UAV-derived 3D point clouds can provide fast information on the damage situation after an earthquake. However, the assessment of multiple damage grades is challenging due to the variety in damage…

Computer Vision and Pattern Recognition · Computer Science 2023-02-27 Vivien Zahs , Katharina Anders , Julia Kohns , Alexander Stark , Bernhard Höfle