Estimating Rainfall Erosivity in North Korea Using Automated Machine Learning: Insights into Regional Soil Erosion Risks

Estimating Rainfall Erosivity in North Korea Using Automated Machine Learning: Insights into Regional Soil Erosion Risks

Soil erosion due to rainfall is a critical environmental issue in North Korea, exacerbated by deforestation and climate change. This study aims to estimate rainfall erosivity (RE) in North Korea using automated machine learning (AutoML), with a particular focus on regional soil erosion risks. North...

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Bibliographic Details
Main Authors: Jeongho Han, Seoro Lee
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Land
Subjects:
rainfall erosivity
RUSLE
machine learning
soil erosion
North Korea
automated machine learning
Online Access:https://www.mdpi.com/2073-445X/13/12/2038
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