Flood inundation prediction
PD Bates - Annual Review of Fluid Mechanics, 2022 - annualreviews.org
Every year flood events lead to thousands of casualties and significant economic damage.
Mapping the areas at risk of flooding is critical to reducing these losses, yet until the last few …
Mapping the areas at risk of flooding is critical to reducing these losses, yet until the last few …
Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources
This paper reviews the most important information fusion data-driven algorithms based on
Machine Learning (ML) techniques for problems in Earth observation. Nowadays we …
Machine Learning (ML) techniques for problems in Earth observation. Nowadays we …
Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data
AM Abdi - GIScience & Remote Sensing, 2020 - Taylor & Francis
In recent years, the data science and remote sensing communities have started to align due
to user-friendly programming tools, access to high-end consumer computing power, and the …
to user-friendly programming tools, access to high-end consumer computing power, and the …
Combined modeling of US fluvial, pluvial, and coastal flood hazard under current and future climates
This study reports a new and significantly enhanced analysis of US flood hazard at 30 m
spatial resolution. Specific improvements include updated hydrography data, new methods …
spatial resolution. Specific improvements include updated hydrography data, new methods …
Recent advances and new frontiers in riverine and coastal flood modeling
K Jafarzadegan, H Moradkhani… - Reviews of …, 2023 - Wiley Online Library
Over the past decades, the scientific community has made significant efforts to simulate
flooding conditions using a variety of complex physically based models. Despite all …
flooding conditions using a variety of complex physically based models. Despite all …
[HTML][HTML] Flooding and its relationship with land cover change, population growth, and road density
Bangladesh experiences frequent hydro-climatic disasters such as flooding. These disasters
are believed to be associated with land use changes and climate variability. However …
are believed to be associated with land use changes and climate variability. However …
Assessment of urban flood susceptibility using semi-supervised machine learning model
In order to identify flood-prone areas with limited flood inventories, a semi-supervised
machine learning model—the weakly labeled support vector machine (WELLSVM)—is used …
machine learning model—the weakly labeled support vector machine (WELLSVM)—is used …
Comparative assessment of the flash-flood potential within small mountain catchments using bivariate statistics and their novel hybrid integration with machine …
R Costache, H Hong, QB Pham - Science of the Total Environment, 2020 - Elsevier
The present study is carried out in the context of the continuous increase, worldwide, of the
number of flash-floods phenomena. Also, there is an evident increase of the size of the …
number of flash-floods phenomena. Also, there is an evident increase of the size of the …
Human alterations of the global floodplains 1992–2019
Floodplains provide critical ecosystem services; however, loss of natural floodplain functions
caused by human alterations increase flood risks and lead to massive loss of life and …
caused by human alterations increase flood risks and lead to massive loss of life and …
A framework for modeling flood depth using a hybrid of hydraulics and machine learning
Solving river engineering problems typically requires river flow characterization, including
the prediction of flow depth, flow velocity, and flood extent. Hydraulic models use governing …
the prediction of flow depth, flow velocity, and flood extent. Hydraulic models use governing …