GIS Model Maps Flood Vulnerability Across Kerala’s Low-Lying Alappuzha Coast
A GIS-based multi-criteria decision analysis framework maps physical flood vulnerability across Alappuzha District, Kerala, and its predictions align strongly with ...
A GIS-based multi-criteria decision analysis framework maps physical flood vulnerability across Alappuzha District, Kerala, and its predictions align strongly with ...
An AHP-GIS study of Sunamganj district in Bangladesh finds that roughly 37 percent of the area falls within high or ...
A new GIS-based study of Malaysia's Langat Catchment combines flood and landslide susceptibility into a single multi-hazard map, classifying 30.9 ...
A district-scale study in Somalia combined satellite validation, 14 conditioning factors and ensemble machine learning to map flood susceptibility across ...
A new machine learning study maps Nepal nationwide flood and landslide susceptibility and identifies thousands of square kilometres of connected ...
A GIS and analytical hierarchy process study of Ilorin, Nigeria, has mapped flood susceptibility across the entire metropolis and found ...
Researchers in Nigeria combined satellite data with a structured expert-weighting method to map flood susceptibility across Makurdi, finding that over ...
Satellite records show Port-au-Prince's built-up area more than quadrupled between 2015 and 2025, converting the vegetated slopes that regulate runoff ...
Researchers used MaxEnt, SVM, and neural network models trained on real check dam and flood records to map optimal conservation ...
Researchers fused morphometric basin analysis with machine learning to map flood susceptibility across four Bayelsa State catchments, revealing hidden high-risk ...
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© 2025 Scienmag - Science Magazine