Choosing the Right Horizontal Resolution for Gully Erosion Susceptibility Mapping Using Machine Learning Algorithms: A Case in Highly Complex Terrain

Choosing the Right Horizontal Resolution for Gully Erosion Susceptibility Mapping Using Machine Learning Algorithms: A Case in Highly Complex Terrain

Gully erosion susceptibility (GES) maps are essential for managing land resources and erosion control. Choosing the optimal horizontal resolution in GES mapping is a challenge. In this study, the optimal resolution for GES mapping in a complex loess hilly area on the Chinese Loess Plateau was tested...

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Bibliographic Details
Main Authors: Annan Yang, Chunmei Wang, Qinke Yang, Guowei Pang, Yongqing Long, Lei Wang, Lijuan Yang, Richard M. Cruse
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Remote Sensing
Subjects:
gully erosion
resolution
machine learning
influencing factor
Loess Plateau
Online Access:https://www.mdpi.com/2072-4292/14/11/2580

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