Machine learning combined with geodetector to predict the spatial distribution of soil heavy metals in mining areas

An accurate understanding of the spatial distribution of soil heavy metals (HMs) is crucial for the effective prevention of soil pollution and remediation strategies. Traditional machine learning models often overlook the spatially stratified heterogeneity inherent to environmental data, which can i...

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Veröffentlicht in:	The Science of the total environment 2025-01, Vol.959, p.178281, Article 178281
Hauptverfasser:	Hu, Haolong, Zhou, Wei, Liu, Xiaoyang, Guo, Guanlin, He, Yinhai, Zhu, Leming, Chen, Dandan, Miao, Ruixue
Format:	Artikel
Sprache:	eng
Schlagworte:	Geodetector Machine learning Soil heavy metals Spatial heterogeneity Spatial prediction
Online-Zugang:	Volltext
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