Cited by Research Progress and Prospects of Urban Flooding Simulation: From Traditional Numerical Models to Deep Learning Approaches

Hybrid approach for flood susceptibility assessment in a flood-prone mountainous catchment in China DOI

Lei Fang, Jinliang Huang,

Juntao Cai

et al.

Journal of Hydrology, Journal Year: 2022, Volume and Issue: 612, P. 128091 - 128091

Published: June 27, 2022

Language: Английский

Citations

An urban DEM reconstruction method based on multisource data fusion for urban pluvial flooding simulation DOI

Haocheng Huang, Weihong Liao,

Xiaohui Lei

et al.

Journal of Hydrology, Journal Year: 2022, Volume and Issue: 617, P. 128825 - 128825

Published: Nov. 28, 2022

Language: Английский

Citations

An Effective Approach for Automatic River Features Extraction Using High-Resolution UAV Imagery DOI

Marco La Salandra, Rosa Colacicco, Pierfrancesco Dellino

et al.

Drones, Journal Year: 2023, Volume and Issue: 7(2), P. 70 - 70

Published: Jan. 18, 2023

The effects of climate change are causing an increase in the frequency and extent natural disasters. Because their morphological characteristics, rivers can cause major flooding events. Indeed, they be subjected to variations discharge response heavy rainfall riverbank failures. Among emerging methodologies that address monitoring river flooding, those include combination Unmanned Aerial Vehicle (UAV) photogrammetric techniques (i.e., Structure from Motion-SfM) ensure high-frequency acquisition high-resolution spatial data over wide areas so generation orthomosaics, useful for automatic feature extraction. Trainable Weka Segmentation (TWS) is extraction open-source tool. It was developed primarily fulfill supervised classification purposes biological microscope images, but its usefulness has been demonstrated several image pipelines. At same time, there a significant lack published studies on applicability TWS with identification universal efficient machine learning classifiers segmentation approach, particular respect classifying UAV images riverine environments. In this perspective, we present study comparing accuracy nine combinations, classifier plus filter, using TWS, also human photo-interpretation, order identify effective approach features multi-temporal orthomosaics. results, which very close interpretation, indicate proposed could prove valuable tool support improve hydro-geomorphological hazard assessments

Language: Английский

Citations

Daily Scale River Flow Forecasting Using Hybrid Gradient Boosting Model with Genetic Algorithm Optimization DOI

Hüseyin Çağan Kılınç, Iman Ahmadianfar, Vahdettin Demir

et al.

Water Resources Management, Journal Year: 2023, Volume and Issue: 37(9), P. 3699 - 3714

Published: May 3, 2023

Language: Английский

Citations

Research Progress and Prospects of Urban Flooding Simulation: From Traditional Numerical Models to Deep Learning Approaches DOI

Bowei Zeng,

Guoru Huang, Wenjie Chen

et al.

Environmental Modelling & Software, Journal Year: 2024, Volume and Issue: unknown, P. 106213 - 106213

Published: Sept. 1, 2024

Language: Английский

Citations