The state of the art in deep learning applications, challenges, and future prospects: A comprehensive review of flood forecasting and management
Floods are a devastating natural calamity that may seriously harm both infrastructure and
people. Accurate flood forecasts and control are essential to lessen these effects and …
people. Accurate flood forecasts and control are essential to lessen these effects and …
Effective delineation of rare metal-bearing granites from remote sensing data using machine learning methods: A case study from the Umm Naggat Area, Central …
MA Abdelkader, Y Watanabe, A Shebl… - Ore Geology …, 2022 - Elsevier
Albitized granite (ABG) is considered as one of the most significant hosts of rare metals
(RMs). Consequently, adequate recognition of ABG through proper lithological …
(RMs). Consequently, adequate recognition of ABG through proper lithological …
[HTML][HTML] Multi-hazard susceptibility mapping based on Convolutional Neural Networks
Multi-hazard susceptibility prediction is an important component of disasters risk
management plan. An effective multi-hazard risk mitigation strategy includes assessing …
management plan. An effective multi-hazard risk mitigation strategy includes assessing …
Comparison of machine learning algorithms for flood susceptibility mapping
Floods are one of the most destructive natural disasters, causing financial and human losses
every year. As a result, reliable Flood Susceptibility Mapping (FSM) is required for effective …
every year. As a result, reliable Flood Susceptibility Mapping (FSM) is required for effective …
Cross-modal change detection flood extraction based on convolutional neural network
X He, S Zhang, B Xue, T Zhao, T Wu - International Journal of Applied Earth …, 2023 - Elsevier
Flood events are often accompanied by rainy weather, which limits the applicability of optical
satellite images, whereas synthetic aperture radar (SAR) is less sensitive to weather and …
satellite images, whereas synthetic aperture radar (SAR) is less sensitive to weather and …
Application of GIS and IoT Technology based MCDM for Disaster Risk Management: Methods and Case Study
NM AbdelAziz, KA Eldrandaly… - … in Management and …, 2024 - dmame-journal.org
This study proposes a two-phase framework to enhance disaster management strategies for
flooding using Geographic Information System (GIS) and Internet of Things (IoT) real-time …
flooding using Geographic Information System (GIS) and Internet of Things (IoT) real-time …
Flood susceptibility mapping using AutoML and a deep learning framework with evolutionary algorithms for hyperparameter optimization
Flooding is one of the most common natural hazards that have extremely detrimental
consequences. Understanding which areas are vulnerable to flooding is crucial to …
consequences. Understanding which areas are vulnerable to flooding is crucial to …
Applying a 1D convolutional neural network in flood susceptibility assessments—The case of the Island of Euboea, Greece
The main scope of the study is to evaluate the prognostic accuracy of a one-dimensional
convolutional neural network model (1D-CNN), in flood susceptibility assessment, in a …
convolutional neural network model (1D-CNN), in flood susceptibility assessment, in a …
A multi-criteria decision analysis (MCDA) approach for landslide susceptibility mapping of a part of Darjeeling District in North-East Himalaya, India
Landslides are the nation's hidden disaster, significantly increasing economic loss and
social disruption. Unfortunately, limited information is available about the depth and extent of …
social disruption. Unfortunately, limited information is available about the depth and extent of …
The quantitative assessment of impact of pumping capacity and LID on urban flood susceptibility based on machine learning
Y Wu, D She, J Xia, J Song, T Xiao, Y Zhou - Journal of Hydrology, 2023 - Elsevier
Drainage facilities such as drainage pumping systems and Low Impact Development (LID)
practices are effective measures to reduce urban flood risk. The quantitative identification of …
practices are effective measures to reduce urban flood risk. The quantitative identification of …