Deep learning methods for flood mapping: a review of existing applications and future research directions
Deep Learning techniques have been increasingly used in flood management to overcome
the limitations of accurate, yet slow, numerical models, and to improve the results of …
the limitations of accurate, yet slow, numerical models, and to improve the results of …
Artificial neural network approaches for disaster management: A literature review
Disaster management (DM) is one of the leading fields that deal with the humanitarian
aspects of emergencies. The field has attracted researchers because of its ever-increasing …
aspects of emergencies. The field has attracted researchers because of its ever-increasing …
Flood susceptibility modeling in Teesta River basin, Bangladesh using novel ensembles of bagging algorithms
The flooding in Bangladesh during monsoon season is very common and frequently
happens. Consequently, people have been experiencing tremendous damage to properties …
happens. Consequently, people have been experiencing tremendous damage to properties …
Flood susceptibility mapping through the GIS-AHP technique using the cloud
KC Swain, C Singha, L Nayak - ISPRS International Journal of Geo …, 2020 - mdpi.com
Flood susceptibility mapping is essential for characterizing flood risk zones and for planning
mitigation approaches. Using a multi-criteria decision support system, this study investigated …
mitigation approaches. Using a multi-criteria decision support system, this study investigated …
GIS-based flood hazard mapping using relative frequency ratio method: A case study of Panjkora River Basin, eastern Hindu Kush, Pakistan
K Ullah, J Zhang - Plos one, 2020 - journals.plos.org
Flood is the most devastating and prevalent disaster among all-natural disasters. Every year,
flood claims hundreds of human lives and causes damage to the worldwide economy and …
flood claims hundreds of human lives and causes damage to the worldwide economy and …
Groundwater level modeling using augmented artificial ecosystem optimization
Nature-inspired optimization is an active area of research in the artificial intelligence (AI)
field and has recently been adopted in hydrology for the calibration (training) of both process …
field and has recently been adopted in hydrology for the calibration (training) of both process …
Enhancing flood susceptibility modeling using multi-temporal SAR images, CHIRPS data, and hybrid machine learning algorithms
Flood susceptibility maps are useful tool for planners and emergency management
professionals in the early warning and mitigation stages of floods. In this study, Sentinel-1 …
professionals in the early warning and mitigation stages of floods. In this study, Sentinel-1 …
Deep neural network utilizing remote sensing datasets for flood hazard susceptibility mapping in Brisbane, Australia
Large damages and losses resulting from floods are widely reported across the globe. Thus,
the identification of the flood-prone zones on a flood susceptibility map is very essential. To …
the identification of the flood-prone zones on a flood susceptibility map is very essential. To …
A novel approach to flood risk assessment: Synergizing with geospatial based MCDM-AHP model, multicollinearity, and sensitivity analysis in the Lower Brahmaputra …
Floods persist as a recurring and daunting peril in the Brahmaputra plain of Assam.
Notwithstanding advancement, Bongaigaon is a highly flood-afflicted district in the lower part …
Notwithstanding advancement, Bongaigaon is a highly flood-afflicted district in the lower part …
A comparison of performance measures of three machine learning algorithms for flood susceptibility mapping of river Silabati (tropical river, India)
Flood is the most common phenomenon causing extensive disruption to the environment,
socio-economy, infrastructure and many other aspects of human life. Flood susceptibility …
socio-economy, infrastructure and many other aspects of human life. Flood susceptibility …