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Rapid earthquake magnitude estimation is crucial for effective early warning systems that can save lives and reduce economic damage. In this paper, we present a comprehensive study of magnitude classification using only the vertical…

This paper addresses a missing capability in infrastructure resilience: turning fast, global AI weather forecasts into asset-scale, actionable risk. We introduce the AI-based Correction-Downscaling Framework (ACDF), which transforms coarse…

Systems and Control · Electrical Eng. & Systems 2026-03-16 You Wu , Zhenguo Wang , Naiyu Wang

A recently proposed method of constructing seismic networks from 'record breaking events' from the earthquake catalog of California (Phy. Rev. E, 77 6,066104, 2008) was successfull in establishing causal features to seismicity and arrive at…

Geophysics · Physics 2017-08-02 P. G. Revathi , T. R. Krishnamohan

In 2021, Japan recorded more than three times as much snowfall as usual, so road user maybe come across dangerous situation. The poor visibility caused by snow triggers traffic accidents. For example, 2021 January 19, due to the dry snow…

Computer Vision and Pattern Recognition · Computer Science 2021-03-02 Takato Yasuno , Hiroaki Sugawara , Junichiro Fujii , Ryuto Yoshida

In order to respond effectively in the aftermath of a disaster, emergency services and relief organizations rely on timely and accurate information about the affected areas. Remote sensing has the potential to significantly reduce the time…

With increasing urbanization, in recent years there has been a growing interest and need in monitoring and analyzing urban flood events. Social media, as a new data source, can provide real-time information for flood monitoring. The social…

Computer Vision and Pattern Recognition · Computer Science 2020-10-13 Yu Feng , Claus Brenner , Monika Sester

This study introduces a novel dataset for segmenting flooded areas in satellite images. After reviewing 77 existing benchmarks utilizing satellite imagery, we identified a shortage of suitable datasets for this specific task. To fill this…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Youngsun Jang , Dongyoun Kim , Chulwoo Pack , Kwanghee Won

Timely disaster risk management requires accurate road maps and prompt damage assessment. Currently, this is done by volunteers manually marking satellite imagery of affected areas but this process is slow and often error-prone.…

Computer Vision and Pattern Recognition · Computer Science 2020-06-11 Ananya Gupta , Elisabeth Welburn , Simon Watson , Hujun Yin

Vulnerability and risk assessment of neighborhoods is essential for effective disaster preparedness. Existing traditional systems, due to dependency on time-consuming and cost-intensive field surveying, do not provide a scalable way to…

Research on damage detection of road surfaces using image processing techniques has been actively conducted, achieving considerably high detection accuracies. Many studies only focus on the detection of the presence or absence of damage.…

Computer Vision and Pattern Recognition · Computer Science 2020-01-24 Hiroya Maeda , Yoshihide Sekimoto , Toshikazu Seto , Takehiro Kashiyama , Hiroshi Omata

Climate change is a major threat to humanity, and the actions required to prevent its catastrophic consequences include changes in both policy-making and individual behaviour. However, taking action requires understanding the effects of…

UAVs are playing an increasingly important role in the field of wilderness rescue by virtue of their flexibility. This paper proposes a fusion of UAV vision technology and satellite image analysis technology for active wildfires detection…

Artificial Intelligence · Computer Science 2023-12-07 Chang Liu , Tamas Sziranyi

This paper introduces a probabilistic framework to quantify community vulnerability towards power losses due to extreme weather events. To analyze the impact of weather events on the power grid, the wind fields of historical hurricanes from…

Systems and Control · Electrical Eng. & Systems 2023-11-28 Abodh Poudyal , Shishir Lamichhane , Charlotte Wertz , Sajjad Uddin Mahmud , Anamika Dubey

The analysis of natural disasters such as floods in a timely manner often suffers from limited data due to a coarse distribution of sensors or sensor failures. This limitation could be alleviated by leveraging information contained in…

Information Retrieval · Computer Science 2020-03-24 Björn Barz , Kai Schröter , Moritz Münch , Bin Yang , Andrea Unger , Doris Dransch , Joachim Denzler

Foehn winds, characterized by abrupt temperature increases and wind speed changes, significantly impact regions on the leeward side of mountain ranges, e.g., by spreading wildfires. Understanding how foehn occurrences change under climate…

Applications · Statistics 2024-11-07 Reto Stauffer , Achim Zeileis , Georg J. Mayr

Image data has a great potential of helping post-earthquake visual inspections of civil engineering structures due to the ease of data acquisition and the advantages in capturing visual information. A variety of techniques have been applied…

Computer Vision and Pattern Recognition · Computer Science 2018-05-17 Yasutaka Narazaki , Vedhus Hoskere , Tu A. Hoang , Billie F. Spencer

Pavement condition evaluation is essential to time the preventative or rehabilitative actions and control distress propagation. Failing to conduct timely evaluations can lead to severe structural and financial loss of the infrastructure and…

Computer Vision and Pattern Recognition · Computer Science 2020-12-18 Sadra Naddaf-Sh , M-Mahdi Naddaf-Sh , Amir R. Kashani , Hassan Zargarzadeh

Environmental disasters such as floods, hurricanes, and wildfires have increasingly threatened communities worldwide, prompting various mitigation strategies. Among these, property buyouts have emerged as a prominent approach to reducing…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Hakan T. Otal , Elyse Zavar , Sherri B. Binder , Alex Greer , M. Abdullah Canbaz

Purpose of review: This paper presents a review of the current state of the art in remote sensing based monitoring of forest disturbances and forest degradation from optical Earth Observation data. Part one comprises an overview of…

Computer Vision and Pattern Recognition · Computer Science 2017-03-23 Manuela Hirschmugl , Heinz Gallaun , Matthias Dees , Pawan Datta , Janik Deutscher , Nikos Koutsias , Mathias Schardt

Deforestation estimation and fire detection in the Amazon forest poses a significant challenge due to the vast size of the area and the limited accessibility. However, these are crucial problems that lead to severe environmental…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Gabor Fodor , Marcos V. Conde