[PDF][PDF] Deep Learning Methods of Satellite Image Processing for Monitoring of Flood Dynamics in the Ganges Delta, Bangladesh. Water 2024, 16, 1141

P Lemenkova - 2024 - academia.edu
Mapping spatial data is essential for the monitoring of flooded areas, prognosis of hazards
and prevention of flood risks. The Ganges River Delta, Bangladesh, is the world's largest …

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

P Lemenkova - Water, 2024 - mdpi.com
Mapping spatial data is essential for the monitoring of flooded areas, prognosis of hazards
and prevention of flood risks. The Ganges River Delta, Bangladesh, is the world's largest …

Flood Forecasting Using Artificial Neural Network (ANNs): A Case study of Jamuna River

MTR Mazumder, BC Gupta - AGU Fall Meeting Abstracts, 2021 - ui.adsabs.harvard.edu
Jamuna is one of the major rivers in Bangladesh which is highly vulnerable to floods.
Bangladesh has faced devastating floods during recent years. As the physical processes …

Delineating flood zones upon employing synthetic aperture data for the 2020 flood in Bangladesh

MA Aziz, M Moniruzzaman, A Tripathi… - Earth Systems and …, 2022 - Springer
Delineating a flood map is critical to perceive the potential risks of the event at diverse
communities living both in urban and rural settings in Bangladesh. A timely generated flood …

Flood Hazard and Natural Risk Assessment: A Case Study of Bangladesh

P Lemenkova - 2024 - hal.science
This work presents a case study of floods in Bangladesh using GIS analysis and deep
learning. Floods are the natural hazard with the globe coverage and high frequency. Flood …

Empowering real-time flood impact assessment through the integration of machine learning and Google Earth Engine: a comprehensive approach

NS Khan, SK Roy, S Talukdar, M Billah, A Iqbal… - … Science and Pollution …, 2024 - Springer
Floods cause substantial losses to life and property, especially in flood-prone regions like
northwestern Bangladesh. Timely and precise evaluation of flood impacts is critical for …

Optimized Deep Learning Model for Flood Detection Using Satellite Images

A Stateczny, HD Praveena, RH Krishnappa… - Remote Sensing, 2023 - mdpi.com
The increasing amount of rain produces a number of issues in Kerala, particularly in urban
regions where the drainage system is frequently unable to handle a significant amount of …

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data

SM Toufique, SU Bhuiyan, A Lateef, A Zaman, JB Islam - 2024 - dspace.bracu.ac.bd
Flooding is a complex phenomenon that, due to its nonlinear and dynamic character, is
difficult to anticipate. As a result, the prediction of floods has emerged as a critical area of …

Hybrid deep learning model for flood frequency assessment and flood forecasting

RP Pandey, M Desai, R Panwar - Multidisciplinary Science Journal, 2023 - malque.pub
The most common and persistent natural hazard to people across the globe is flooding. The
frequency of floods in a given place is defined as the likelihood and intensity of floods …

Geospatial mapping and analysis of the 2019 flood disaster extent and impact in the city of ghat in southwestern Libya using google earth engine and deep learning …

HA Zurqani, A Al-Bukhari, AO Aldaikh, KI Elfadli… - … applications of remote …, 2022 - Springer
Flooding impacts from heavy rainfall, thunderstorm, and other natural hazards are a
significant concern in many areas of the world. The objectives of this study were to:(1) …