Soil Erosion Quantification using Machine Learning in Sub-Watersheds of Northern Portugal

Soil Erosion Quantification using Machine Learning in Sub-Watersheds of Northern Portugal

Protected areas (PA) play an important role in minimizing the effects of soil erosion in watersheds. This study evaluated the performance of machine learning models, specifically support vector machine with linear kernel (SVMLinear), support vector machine with polynomial kernel (SVMPoly), and rando...

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Bibliographic Details
Main Authors: Saulo Folharini, António Vieira, António Bento-Gonçalves, Sara Silva, Tiago Marques, Jorge Novais
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Hydrology
Subjects:
soil erosion
sub-watersheds
machine learning
burned areas
protected areas
Online Access:https://www.mdpi.com/2306-5338/10/1/7

Internet

https://www.mdpi.com/2306-5338/10/1/7

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