Flood conditioning factor maps: LULC and geology.

Flood conditioning factor maps: LULC and geology.

<p>(This map has been created by the author using ArcGIS Software: ESRI ArcGIS Pro v3.0.1 x64).</p>

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Bibliographic Details
Main Author:	Tahmina Afrose Keya (20141592) (author)
Other Authors:	Siventhiran S. Balakrishnan (20141595) (author), Maheswaran Solayappan (20141598) (author), Saravana Selvan Dheena Dhayalan (20141601) (author), Sreeramanan Subramaniam (466365) (author), Low Jun An (20141604) (author), Anthony Leela (20141607) (author), Kevin Fernandez (20141610) (author), Prahan Kumar (20141613) (author), A. Lokeshmaran (20141616) (author), Abhijit Vinodrao Boratne (20141619) (author), Mohd Tajuddin Abdullah (10147568) (author)
Published:	2024
Subjects:	Biotechnology Ecology Plant Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified xlink "> malaysia standard statistical measures improve flood management geographic information system flood vulnerability assessment flood susceptibility models flood susceptibility mapping flood susceptibility map flood influencing factors expertise provide opportunities ensemble machine learning dense tree canopies class collectively made causing significant damage abundant flooded vegetation patterns ranking subsequently high &# 8217 pahang &# 8217 1 x64 ). fs ranking demonstrated &# 8217 high risk gis ). particularly pahang pahang found validation datasets technological advancements steep inclines sophisticated methods random forest primary attributes lying topography less susceptible land use land cover intense precipitation geospatial database flow direction flow accumulation feature selection central regions better prepared bare ground arcgis software algorithm based
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