Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gully erosion

Published 2019 View Full Article

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Title
Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gully erosion
Authors
Keywords
Discrimination, Gully erosion susceptibility, Machine learning models, Reliability, Latin hypercube sampling technique (cLHS), Topographic attributes
Journal
SCIENCE OF THE TOTAL ENVIRONMENT
Volume 664, Issue -, Pages 1117-1132
Publisher
Elsevier BV
Online
2019-02-08
DOI
10.1016/j.scitotenv.2019.02.093

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