Stakeholder analysis in the application of cutting-edge digital visualisation technologies for urban flood risk management: A critical review

Expert Systems with Applications, Год журнала: 2023, Номер 236, С. 121426 - 121426

Опубликована: Сен. 4, 2023

Cutting-edge flood visualisation technologies are becoming increasingly important in managing urban risks, particularly from the perspective of stakeholders who play a crucial role controlling and reducing risks associated with events. This review study provides comprehensive overview stakeholder analysis this context, highlighting gaps current research paving way for future investigations. For purpose, scientific literature critical conducted based on identified relevant works to map mutual context. categorises cutting-edge into four groups - virtual reality, augmented mixed digital twin explores their adoption engaging various across five key stages risk management: prevention, mitigation, preparation, response, recovery. Results show that existing has primarily concentrated support water utilities communication general public. However, there is noticeable gap regarding engagement such as policy-makers, researchers, insurance providers. Furthermore, highlights disparities involvement damage assessment studies, lack representation policy-makers researchers. Finally, introduces concept overlooked interconnected impacts they have, which received relatively little attention previous research.

Язык: Английский

---

Improving urban flood prediction using LSTM-DeepLabv3+ and Bayesian optimization with spatiotemporal feature fusion

Journal of Hydrology, Год журнала: 2024, Номер 630, С. 130743 - 130743

Опубликована: Янв. 26, 2024

Язык: Английский

---

Flood risk assessment of urban metro system using random forest algorithm and triangular fuzzy number based analytical hierarchy process approach

Sustainable Cities and Society, Год журнала: 2024, Номер 109, С. 105546 - 105546

Опубликована: Май 21, 2024

Язык: Английский

---

A Novel Multi-Scenario Mitigation Model for Rainstorm Flood Disasters

International Journal of Disaster Risk Reduction, Год журнала: 2025, Номер 119, С. 105321 - 105321

Опубликована: Фев. 18, 2025

Язык: Английский

---

Prediction of flood risk levels of urban flooded points though using machine learning with unbalanced data

Journal of Hydrology, Год журнала: 2024, Номер 630, С. 130742 - 130742

Опубликована: Янв. 25, 2024

Язык: Английский

---

Threshold and real-time initiation mechanism of urban flood emergency response under combined disaster scenarios

Sustainable Cities and Society, Год журнала: 2024, Номер 108, С. 105512 - 105512

Опубликована: Май 8, 2024

Язык: Английский

---

Enhancing transparency in data-driven urban pluvial flood prediction using an explainable CNN model

Journal of Hydrology, Год журнала: 2024, Номер unknown, С. 132228 - 132228

Опубликована: Окт. 1, 2024

Язык: Английский

---

Geographic heterogeneity of activation functions in urban real-time flood forecasting: Based on seasonal trend decomposition using Loess-Temporal Convolutional Network-Gated Recurrent Unit model

Journal of Hydrology, Год журнала: 2024, Номер 636, С. 131279 - 131279

Опубликована: Май 7, 2024

Язык: Английский

---

Assessment of the jacking effect of high tide on compound flooding in a coastal city under sea level rise based on water tracer modeling

Journal of Hydrology, Год журнала: 2023, Номер 627, С. 130474 - 130474

Опубликована: Ноя. 14, 2023

Язык: Английский

---

Integrating Machine Learning Models with Comprehensive Data Strategies and Optimization Techniques to Enhance Flood Prediction Accuracy: A Review

Water Resources Management, Год журнала: 2024, Номер 38(12), С. 4735 - 4761

Опубликована: Июнь 3, 2024

Язык: Английский

---