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Comparison of machine learning models for gully erosion susceptibility mapping

2020

© 2019 China University of Geosciences (Beijing) and Peking University Gully erosion is a disruptive phenomenon which extensively affects the Iranian territory, especially in the Northern provinces. A number of studies have been recently undertaken to study this process and to predict it over space and ultimately, in a broader national effort, to limit its negative effects on local communities. We focused on the Bastam watershed where 9.3% of its surface is currently affected by gullying. Machine learning algorithms are currently under the magnifying glass across the geomorphological community for their high predictive ability. However, unlike the bivariate statistical models, their structu…

Watershed010504 meteorology & atmospheric sciencesComputer scienceBivariate analysisLogistic model tree model010502 geochemistry & geophysicsMachine learningcomputer.software_genre01 natural sciencesLogistic model treeNatural hazardEntropy (information theory)Oil erosion0105 earth and related environmental sciencesbusiness.industrylcsh:QE1-996.5Statistical modelGISlcsh:GeologyITC-ISI-JOURNAL-ARTICLEGeneral Earth and Planetary SciencesAlternating decision treeAlternating decision tree modelArtificial intelligenceITC-GOLDbusinesscomputerDecision tree modelGeoscience Frontiers
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