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Earth observation technologies, such as optical imaging and synthetic aperture radar (SAR), provide excellent means to monitor ever-growing urban environments continuously. Notably, in the case of large-scale disasters (e.g., tsunamis and…

Computer Vision and Pattern Recognition · Computer Science 2020-09-15 Bruno Adriano , Naoto Yokoya , Junshi Xia , Hiroyuki Miura , Wen Liu , Masashi Matsuoka , Shunichi Koshimura

Low-latency delivery of satellite imagery is essential for time-critical applications such as disaster response, intelligence, and infrastructure monitoring. However, traditional pipelines rely on downlinking all captured images before…

Machine Learning · Computer Science 2026-04-21 Ansel Kaplan Erol , Seungjun Lee , Divya Mahajan

Rapid damage assessment is of crucial importance to emergency responders during hurricane events, however, the evaluation process is often slow, labor-intensive, costly, and error-prone. New advances in computer vision and remote sensing…

Computer Vision and Pattern Recognition · Computer Science 2018-12-14 Sean Andrew Chen , Andrew Escay , Christopher Haberland , Tessa Schneider , Valentina Staneva , Youngjun Choe

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

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-based onboard data processing is crucial for time-sensitive applications requiring timely and efficient rapid response. Advances in edge artificial intelligence are shifting computational power from ground-based centers to…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Roberto Del Prete , Manuel Salvoldi , Domenico Barretta , Nicolas Longépé , Gabriele Meoni , Arnon Karnieli , Maria Daniela Graziano , Alfredo Renga

Earth Observation (EO) systems are crucial for cartography, disaster surveillance, and resource administration. Nonetheless, they encounter considerable obstacles in the processing and transmission of extensive data, especially in…

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

Existing data on building destruction in conflict zones rely on eyewitness reports or manual detection, which makes it generally scarce, incomplete and potentially biased. This lack of reliable data imposes severe limitations for media…

General Economics · Economics 2021-07-07 Hannes Mueller , Andre Groger , Jonathan Hersh , Andrea Matranga , Joan Serrat

Rapid building damage assessment is critical for post-disaster response. Damage classification models built on satellite imagery provide a scalable means of obtaining situational awareness. However, label noise and severe class imbalance in…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Smriti Siva , Jan Cross-Zamirski

Segmentation of Earth observation (EO) satellite data is critical for natural hazard analysis and disaster response. However, processing EO data at ground stations introduces delays due to data transmission bottlenecks and communication…

Machine Learning · Computer Science 2024-11-28 Meghan Plumridge , Rasmus Maråk , Chiara Ceccobello , Pablo Gómez , Gabriele Meoni , Filip Svoboda , Nicholas D. Lane

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

Driven by the growing demand for intelligent remote sensing applications, large artificial intelligence (AI) models pre-trained on large-scale unlabeled datasets and fine-tuned for downstream tasks have significantly improved learning…

Machine Learning · Computer Science 2025-06-24 Yuanming Shi , Jingyang Zhu , Chunxiao Jiang , Linling Kuang , Khaled B. Letaief

Unmanned aerial vehicle-assisted disaster recovery missions have been promoted recently due to their reliability and flexibility. Machine learning algorithms running onboard significantly enhance the utility of UAVs by enabling real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Nethmi S. Hewawiththi , M. Mahesha Viduranga , Vanodhya G. Warnasooriya , Tharindu Fernando , Himal A. Suraweera , Sridha Sridharan , Clinton Fookes

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…

Rapid and accurate estimation of post-earthquake ground failures and building damage is critical for effective post-disaster responses. Progression in remote sensing technologies has paved the way for rapid acquisition of detailed,…

Geophysics · Physics 2024-12-03 Xuechun Li , Susu Xu

Earth observations from low Earth orbit satellites provide vital information for decision makers to better manage time-sensitive events such as natural disasters. For the data to be most effective for first responders, low latency is…

Machine Learning · Computer Science 2025-10-13 Stephen Smith , Cormac Purcell , Zdenka Kuncic

The area affected by the earthquake is vast and often difficult to entirely cover, and the earthquake itself is a sudden event that causes multiple defects simultaneously, that cannot be effectively traced using traditional, manual methods.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Mateusz Żarski , Bartosz Wójcik , Jarosław A. Miszczak , Bartłomiej Blachowski , Mariusz Ostrowski

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

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