Deep Learning Methods of Satellite Image Processing for Monitoring of Flood Dynamics in the Ganges Delta, Bangladesh

Water, Год журнала: 2024, Номер 16(8), С. 1141 - 1141

Опубликована: Апрель 17, 2024

Mapping spatial data is essential for the monitoring of flooded areas, prognosis hazards and prevention flood risks. The Ganges River Delta, Bangladesh, world’s largest river delta prone to floods that impact social–natural systems through losses lives damage infrastructure landscapes. Millions people living in this region are vulnerable repetitive due exposure, high susceptibility low resilience. Cumulative effects monsoon climate, rainfall, tropical cyclones hydrogeologic setting Delta increase probability floods. While engineering methods mitigation include practical solutions (technical construction dams, bridges hydraulic drains), regulation traffic land planning support systems, geoinformation rely on modelling remote sensing (RS) evaluate dynamics hazards. Geoinformation indispensable mapping catchments areas visualization affected regions real-time monitoring, addition implementing developing emergency plans vulnerability assessment warning supported by RS data. In regard, study used monitor southern segment Delta. Multispectral Landsat 8-9 OLI/TIRS satellite images were evaluated (March) post-flood (November) periods analysis extent landscape changes. Deep Learning (DL) algorithms GRASS GIS modules qualitative quantitative as advanced image processing. results constitute a series maps based classified

Язык: Английский

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State-of-the-Art Techniques for Real-Time Monitoring of Urban Flooding: A Review

Water, Год журнала: 2024, Номер 16(17), С. 2476 - 2476

Опубликована: Авг. 30, 2024

In the context of increasing frequency urban flooding disasters caused by extreme weather, accurate and timely identification monitoring flood risks have become increasingly important. This article begins with a bibliometric analysis literature on identification, revealing that since 2017, this area has global research hotspot. Subsequently, it presents systematic review current mainstream technologies, drawing from both traditional emerging data sources, which are categorized into sensor-based (including contact non-contact sensors) big data-based social media surveillance camera data). By analyzing advantages disadvantages each technology their different focuses, paper points out largely emphasizes more “intelligent” technologies. However, these technologies still certain limitations, sensor techniques retain significant in practical applications. Therefore, future risk should focus integrating multiple fully leveraging strengths sources to achieve real-time flooding.

Язык: Английский

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OFPO & KGFPO: Ontology and Knowledge Graph for Flood Process Observation

Environmental Modelling & Software, Год журнала: 2025, Номер unknown, С. 106317 - 106317

Опубликована: Янв. 1, 2025

Язык: Английский

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Flood Monitoring Based on Multi-Source Remote Sensing Data Fusion Driven by HIS-NSCT Model

Water, Год журнала: 2025, Номер 17(3), С. 396 - 396

Опубликована: Янв. 31, 2025

Floods have significant impacts on economic development and cause the loss of both lives property, posing a serious threat to social stability. Effectively identifying evolution patterns floods could enhance role flood monitoring in disaster prevention mitigation. Firstly, this study, we utilized low-cost multi-source multi-temporal remote sensing construct an HIS-NSCT fusion model based SAR optical order obtain best image. Secondly, constructed regional growth accurately identify floods. Finally, extracted analyzed extent, depth, area farmland submerged by flood. The results indicated that maintained spatial characteristics spectral information images well, as determined through subjective objective multi-index evaluations. Moreover, preserve detailed features water body edges, eliminate misclassifications caused terrain shadows, enable effective extraction bodies. Based Poyang Lake, incorporating precipitation, elevation, cultivated land, other data, accurate identification inundation range, inundated land can be achieved. This study provides data technical support for identification, control, relief decision-making, among aspects.

Язык: Английский

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A bottom-up approach of knowledge graph modelling for urban underground public spaces: Insights into public cognition

Tunnelling and Underground Space Technology, Год журнала: 2025, Номер 163, С. 106710 - 106710

Опубликована: Апрель 30, 2025

Язык: Английский

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Enhancing understanding of vulnerability and resilience to flash floods through comparative analysis of multidimensional indices

International Journal of Disaster Risk Reduction, Год журнала: 2025, Номер unknown, С. 105540 - 105540

Опубликована: Май 1, 2025

Язык: Английский

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A novel framework for evidence-based assessment of flood resilience integrating multi-source evidence: A case study of the Yangtze River Economic Belt, China

Ecological Indicators, Год журнала: 2024, Номер 167, С. 112705 - 112705

Опубликована: Окт. 1, 2024

Язык: Английский

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Detection of flood-affected areas using multitemporal remote sensing data: a machine learning approach

Earth Science Informatics, Год журнала: 2024, Номер 18(1)

Опубликована: Дек. 12, 2024

Язык: Английский

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Using social media data to construct and analyze knowledge graph for "7.20" Henan rainstorm flood event

International Journal of Disaster Risk Reduction, Год журнала: 2024, Номер unknown, С. 105129 - 105129

Опубликована: Дек. 1, 2024

Язык: Английский

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Knowledge Management Model for Urban Flood Emergency Response Based on Multimodal Knowledge Graphs

Water, Год журнала: 2024, Номер 16(12), С. 1676 - 1676

Опубликована: Июнь 12, 2024

Recently, frequent flood disasters in China have seriously threatened economic development and public safety. This paper addresses the need for a dynamic urban emergency knowledge management system departments lack of systematic among managers regarding control. A multimodal graph-based model was constructed to enhance decision-making capabilities departments, improve efficiency evacuation, reduce losses from by analyzing shortcomings existing system. An intelligent built. integrates graph technology establish framework It develops simulates proposed model’s application scenarios evacuation using Flocking algorithm on NetLogo platform. Through simulation experiments, practicality effectiveness real disaster situations were examined, particularly simulating crowd behavior. The study found that significantly improves accuracy information speed during responses supports conducting targeted personalized decisions. research provides scientific basis optimize their response strategies serves as reference example management.

Язык: Английский

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