Evaluation of different boosting ensemble machine learning models and novel deep learning and boosting framework for head-cut gully erosion susceptibility

The objective of this study is to assess the gully head-cut erosion susceptibility and identify gully erosion prone areas in the Meimand watershed, Iran. In recent years, this study area has been greatly influenced by several head-cut gullies due to unusual climatic factors and human induced activit...

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Veröffentlicht in:	Journal of environmental management 2021-04, Vol.284, p.112015-112015, Article 112015
Hauptverfasser:	Chen, Wei, Lei, Xinxiang, Chakrabortty, Rabin, Chandra Pal, Subodh, Sahana, Mehebub, Janizadeh, Saeid
Format:	Artikel
Sprache:	eng
Schlagworte:	Climatic factors Conservation of Natural Resources Deep Learning Gully head-cut erosion Humans Iran Machine Learning Predictive accuracy Soil Soil conservation
Online-Zugang:	Volltext
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