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Using GIS, remote sensing, and machine learning to highlight the correlation between the land-use/land-cover changes and flash-flood potential

Catchments; Climate change; Earth (planet); Floods; Image processing; Land use; Machine learning; Multilayer neural networks; Remote sensing; Runoff; Geographically weighted regression; Land use/land cover change; Machine learning techniques; Meteorological phenomena; Multilayer perceptron neural ne...

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Bibliographic Details
Main Authors: Costache R., Pham Q.B., Corodescu-Ro?ca E., C�mpianu C., Hong H., Thuy Linh N.T., Fai C.M., Ahmed A.N., Vojtek M., Pandhiani S.M., Minea G., Ciobotaru N., Popa M.C., Diaconu D.C., Pham B.T.
Other Authors: 55888132500
Format: Article
Published: MDPI AG 2023
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Summary:Catchments; Climate change; Earth (planet); Floods; Image processing; Land use; Machine learning; Multilayer neural networks; Remote sensing; Runoff; Geographically weighted regression; Land use/land cover change; Machine learning techniques; Meteorological phenomena; Multilayer perceptron neural networks; Pearson coefficient; Runoff potentials; Synthetic dynamics; Geographic information systems

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