Detection of surface water and floods with multispectral satellites
The use of multispectral satellite imagery for water monitoring is a fast and cost-effective
method that can benefit from the growing availability of medium–high-resolution and free …
method that can benefit from the growing availability of medium–high-resolution and free …
[HTML][HTML] Flood susceptibility map**: Integrating machine learning and GIS for enhanced risk assessment
Flooding presents a formidable challenge in the United States, endangering lives and
causing substantial economic damage, averaging around $5 billion annually. Addressing …
causing substantial economic damage, averaging around $5 billion annually. Addressing …
Assessment of groundwater quality in arid regions utilizing principal component analysis, GIS, and machine learning techniques
Assessing water quality in arid regions is vital due to scarce resources, impacting health and
sustainable management. This study examines groundwater quality in Assuit Governorate …
sustainable management. This study examines groundwater quality in Assuit Governorate …
Flood susceptible prediction through the use of geospatial variables and machine learning methods
Floods are one of the most perilous natural calamities that cause property destruction and
endanger human life. The spatial patterns of flood susceptibility were assessed in this study …
endanger human life. The spatial patterns of flood susceptibility were assessed in this study …
Potential flood-prone area identification and map** using GIS-based multi-criteria decision-making and analytical hierarchy process in Dega Damot district …
Flood is one of the natural hazards that causes widespread destruction such as huge
infrastructural damages, considerable economic losses, and social disturbances across the …
infrastructural damages, considerable economic losses, and social disturbances across the …
Living with floods using state-of-the-art and geospatial techniques: flood mitigation alternatives, management measures, and policy recommendations
Flood, a distinctive natural calamity, has occurred more frequently in the last few decades all
over the world, which is often an unexpected and inevitable natural hazard, but the losses …
over the world, which is often an unexpected and inevitable natural hazard, but the losses …
Forecasting of flash flood susceptibility map** using random forest regression model and geographic information systems
Flash floods, rapid and devastating inundations of water, are increasingly linked to the
intensifying effects of climate change, posing significant challenges for both vulnerable …
intensifying effects of climate change, posing significant challenges for both vulnerable …
Effects of auxiliary and ancillary data on LULC classification in a heterogeneous environment using optimized random forest algorithm
Land use and land cover (LULC) maps, providing crucial information for monitoring the
Earth's surface, are one of the most essential products for numerous studies. Using only the …
Earth's surface, are one of the most essential products for numerous studies. Using only the …
Water body map** using long time series Sentinel-1 SAR data in Poyang Lake
G Shen, W Fu, H Guo, J Liao - Water, 2022 - mdpi.com
Map** water bodies with a high accuracy is necessary for water resource assessment,
and map** them rapidly is necessary for flood monitoring. Poyang Lake is the largest …
and map** them rapidly is necessary for flood monitoring. Poyang Lake is the largest …
[HTML][HTML] Prediction of carbon dioxide emissions from Atlantic Canadian potato fields using advanced hybridized machine learning algorithms–Nexus of field data and …
In this study, three novel machine learning algorithms of additive regression-random forest
(AR-RF), Iterative Classifier Optimizer (ICO-AR-RF), and multi-scheme (MS-RF) were …
(AR-RF), Iterative Classifier Optimizer (ICO-AR-RF), and multi-scheme (MS-RF) were …