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Related papers: Monitoring the Impacts of a Tailings Dam Failure U…

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In this work we present BrazilDAM, a novel public dataset based on Sentinel-2 and Landsat-8 satellite images covering all tailings dams cataloged by the Brazilian National Mining Agency (ANM). The dataset was built using georeferenced…

Computer Vision and Pattern Recognition · Computer Science 2020-05-14 Edemir Ferreira , Matheus Brito , Remis Balaniuk , Mário S. Alvim , Jefersson A. dos Santos

This work explores the combination of free cloud computing, free open-source software, and deep learning methods to analyse a real, large-scale problem: the automatic country-wide identification and classification of surface mines and…

Computer Vision and Pattern Recognition · Computer Science 2020-07-03 Remis Balaniuk , Olga Isupova , Steven Reece

Slope failures possess destructive power that can cause significant damage to both life and infrastructure. Monitoring slopes prone to instabilities is therefore critical in mitigating the risk posed by their failure. The purpose of slope…

Methodology · Statistics 2023-02-06 Sourav Das , Anuradha Priyadarshana , Stephen Grebby

The Brumadinho dam disaster occurred on the 25 January, 2019 when Dam I, an upstream tailings dam at the Corrego do Feijao iron ore mine, 9 kilometres (5.6 mi) east of Brumadinho, Minas Gerais, Brazil, suffered a catastrophic failure. Over…

Computational Physics · Physics 2019-11-14 Arun Raman , Fei Liu

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

Distributing government relief efforts after a flood is challenging. In India, the crops are widely affected by floods; therefore, making rapid and accurate crop damage assessment is crucial for effective post-disaster agricultural…

Computer Vision and Pattern Recognition · Computer Science 2026-01-08 Sanidhya Ghosal , Anurag Sharma , Sushil Ghildiyal , Mukesh Saini

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

Tailings ponds are places for storing industrial waste. Once the tailings pond collapses, the villages nearby will be destroyed and the harmful chemicals will cause serious environmental pollution. There is an urgent need for a reliable…

Signal Processing · Electrical Eng. & Systems 2022-08-11 Jun Yang , Qing Li , Yixuan Sun

In this paper, the authors aim to combine the latest state of the art models in image recognition with the best publicly available satellite images to create a system for landslide risk mitigation. We focus first on landslide detection and…

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

Landslide inventory maps are crucial to validate predictive landslide models; however, since most mapping methods rely on visual interpretation or expert knowledge, detailed inventory maps are still lacking. This study used a fully…

Image and Video Processing · Electrical Eng. & Systems 2020-07-15 Lucas P. Soares , Helen C. Dias , Carlos H. Grohmann

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

Floods cause extensive global damage annually, making effective monitoring essential. While satellite observations have proven invaluable for flood detection and tracking, comprehensive global flood datasets spanning extended time periods…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Amit Misra , Kevin White , Simone Fobi Nsutezo , William Straka , Juan Lavista

The use of Internet of Things (IoT) technologies is becoming a preferred solution for the assessment of tailings dams' safety. Real-time sensor monitoring proves to be a key tool for reducing the risk related to these ever-evolving…

Computational Engineering, Finance, and Science · Computer Science 2021-06-08 Christina Nasikaa , Pedro Diez , Pierre Gerard , Thierry J. Massart , Sergio Zlotnik

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

Satellite remote sensing presents a cost-effective solution for synoptic flood monitoring, and satellite-derived flood maps provide a computationally efficient alternative to numerical flood inundation models traditionally used. While…

Geophysics · Physics 2022-09-05 Antara Dasgupta , Lasse Hybbeneth , Björn Waske

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

In May 2024, weeks of severe rainfall in Rio Grande do Sul, Brazil caused widespread damage to infrastructure, impacting over 400 cities and 2.3 million people. This study presents the construction of comprehensive telecommunications…

Rapid and accurate building damage assessment in the immediate aftermath of tornadoes is critical for coordinating life-saving search and rescue operations, optimizing emergency resource allocation, and accelerating community recovery.…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Robinson Umeike , Thang Dao , Shane Crawford , John van de Lindt , Blythe Johnston , Wanting , Wang , Trung Do , Ajibola Mofikoya , Sarbesh Banjara , Cuong Pham

We propose a method for causal inference using satellite image time series, in order to determine the treatment effects of interventions which impact climate change, such as deforestation. Simply put, the aim is to quantify the 'before…

Machine Learning · Computer Science 2019-10-28 Vikas Ramachandra
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