Point and pixel inclusive machine learning models for exploring gully erosion susceptibility
Author:
Affiliation:
1. Department of Geography, University of Gour Banga, Malda, West Bengal, India
2. Department of Geography, Gour Mahavidyalaya, Malda, West Bengal, India
Publisher
Informa UK Limited
Subject
Water Science and Technology,Geography, Planning and Development
Link
https://www.tandfonline.com/doi/pdf/10.1080/10106049.2022.2106315
Reference124 articles.
1. Comparison of the effectiveness of GIS-based interpolation methods for estimating the spatial distribution of agrochemical soil properties
2. Gully Erosion Susceptibility Assessment in the Kondoran Watershed Using Machine Learning Algorithms and the Boruta Feature Selection
3. Space applications for drought assessment in Wadi-Dama (West Tabouk), KSA
4. Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms
5. Comparison of machine learning models for gully erosion susceptibility mapping
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