Intelligent Extraction of Terracing Using the ASPP ArrU-Net Deep Learning Model for Soil and Water Conservation on the Loess Plateau

Intelligent Extraction of Terracing Using the ASPP ArrU-Net Deep Learning Model for Soil and Water Conservation on the Loess Plateau

The prevention and control of soil erosion through soil and water conservation measures is crucial. It is imperative to accurately and quickly extract information on these measures in order to understand how their configuration affects the runoff and sediment yield process. In this investigation, in...

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Bibliographic Details
Main Authors: Yinan Wang, Xiangbing Kong, Kai Guo, Chunjing Zhao, Jintao Zhao
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Agriculture
Subjects:
loess plateau
soil and water conservation
terracing measures
deep learning
convolutional neural network
U-Net
Online Access:https://www.mdpi.com/2077-0472/13/7/1283

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https://www.mdpi.com/2077-0472/13/7/1283

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