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Related papers: Vulnerability Liquefaction Mapping in Padang City …

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As a result of extreme weather conditions, such as heavy precipitation, natural hillslopes can fail dramatically; these slope failures can occur on a dry day due to time lags between rainfall and pore-water pressure change at depth, or even…

Disordered Systems and Neural Networks · Physics 2023-07-19 Vrinda Desai , Farnaz Fazelpour , Alexander L. Handwerger , Karen E. Daniels

Full waveform inversion (FWI) is a high-resolution seismic inversion technique popularly used in oil and gas exploration. Traditional FWI employs the $l_2$ norm measurement to minimize the misfit between observed and predicted seismic data.…

Geophysics · Physics 2025-04-03 Liangsheng He , Chao Song , Cai Liu

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

A recent report from the World Meteorological Organization (WMO) highlights that water-related disasters have caused the highest human losses among natural disasters over the past 50 years, with over 91\% of deaths occurring in low-income…

Machine Learning · Computer Science 2025-01-14 Ting-Yu Dai , Hayato Ushijima-Mwesigwa

This study presents an explainable parallel transformer architecture for soil liquefaction prediction that integrates three distinct data streams: spectral seismic encoding, soil stratigraphy tokenization, and site-specific features. The…

Machine Learning · Computer Science 2025-02-19 Sompote Youwai , Tipok Kitkobsin , Sutat Leelataviwat , Pornkasem Jongpradist

Nature disasters play a key role in shaping human-urban infrastructure interactions. Effective and efficient response to natural disasters is essential for building resilience and a sustainable urban environment. Two types of information…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Hao Li , Fabian Deuser , Wenping Yina , Xuanshu Luo , Paul Walther , Gengchen Mai , Wei Huang , Martin Werner

Flooding is one of the most destructive natural hazards worldwide, posing serious risks to ecosystems, infrastructure, and human livelihoods. This study combines Synthetic Aperture Radar (SAR) imagery with environmental and hydrological…

Machine Learning · Computer Science 2025-12-29 Edwin Oluoch Awino , Denis Machanda

Indonesia is one of the world's most densely populated regions and lies among the epicenters of Earth's greatest natural hazards. Effectively reducing the disaster potential of these hazards through resource allocation and preparedness…

Geophysics · Physics 2024-04-23 Raelynn Wonnacott , Dallin Stewart , Jared P Whitehead , Ronald A Harris

This study evaluates the effectiveness of three-dimensional variational (3D-Var) data assimilation coupled with a Rapid Update Cycle (RUC) framework for improving short-range precipitation forecasts over the Indonesian Maritime Continent…

Climate resilience across sectors varies significantly in low-income countries (LICs), with agriculture being the most vulnerable to climate change. Existing studies typically focus on individual countries, offering limited insights into…

Neural and Evolutionary Computing · Computer Science 2025-06-02 Ronald Katende

The increasing frequency and intensity of natural disasters call for rapid and accurate damage assessment. In response, disaster benchmark datasets from high-resolution satellite imagery have been constructed to develop methods for…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Kyeongjin Ahn , Sungwon Han , Sungwon Park , Jihee Kim , Sangyoon Park , Meeyoung Cha

Full-Waveform Inversion (FWI) is a nonlinear iterative seismic imaging technique that, by reducing the misfit between recorded and predicted seismic waveforms, can produce detailed estimates of subsurface geophysical properties.…

Geophysics · Physics 2024-11-22 Vahid Negahdari , Seyed Reza Moghadasi , Mohammad Reza Razvan

This paper aims to detect rice field damage from natural disasters in Bangladesh using high-resolution satellite imagery. The authors developed ground truth data for rice field damage from the field level. At first, NDVI differences before…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Tahmid Alavi Ishmam , Amin Ahsan Ali , Md Ahsraful Amin , A K M Mahbubur Rahman

This study assesses landslide vulnerability in the Chittagong Hill Tracts (CHT), specifically focusing on Bandarban district in Southeast Bangladesh. By employing a multidisciplinary approach, thirteen factors influencing landslides were…

Computers and Society · Computer Science 2024-07-31 Nafis Fuad , Javed Meandad , Ashraful Haque , Rukhsar Sultana , Sumaiya Binte Anwar , Sharmin Sultana

Climate change results in an increased probability of extreme weather events that put societies and businesses at risk on a global scale. Therefore, near real-time mapping of natural hazards is an emerging priority for the support of…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Johannes Jakubik , Michal Muszynski , Michael Vössing , Niklas Kühl , Thomas Brunschwiler

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

The frequency of extreme flood events is increasing throughout the world. Daily, high-resolution (30m) Flood Inundation Maps (FIM) observed from space play a key role in informing mitigation and preparedness efforts to counter these extreme…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Akshay Aravamudan , Zimeena Rasheed , Xi Zhang , Kira E. Scarpignato , Efthymios I. Nikolopoulos , Witold F. Krajewski , Georgios C. Anagnostopoulos

The assessment of seismic risk in urban areas with high seismicity is certainly one of the most important problems that territorial managers have to face. A reliable evaluation of this risk is the basis for the design of both specific…

A new approach to seismic interpretation is proposed to leverage visual perception and human visual system modeling. Specifically, a saliency detection algorithm based on a novel attention model is proposed for identifying subsurface…

Computer Vision and Pattern Recognition · Computer Science 2022-01-19 Muhammad Amir Shafiq , Zhiling Long , Haibin Di , Ghassan AlRegib

This work aims to produce landslide density estimates using Synthetic Aperture Radar (SAR) satellite imageries to prioritise emergency resources for rapid response. We use the United States Geological Survey (USGS) Landslide Inventory data…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Vanessa Boehm , Wei Ji Leong , Ragini Bal Mahesh , Ioannis Prapas , Edoardo Nemni , Freddie Kalaitzis , Siddha Ganju , Raul Ramos-Pollán