Predicting soil chemical characteristics in the arid region of central Iran using remote sensing and machine learning models

Predicting soil chemical characteristics in the arid region of central Iran using remote sensing and machine learning models

Abstract Digital Soil Mapping (DSM) techniques have advanced significantly in recent decades, helping to close critical gaps in soil data and knowledge. This study was conducted in the arid Gavkhouni sub-basin of Isfahan Province, central Iran, where environmental stresses such as salinity and water...

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Bibliographic Details
Main Authors: Azita Molaeinasab, Hossein Bashari, Mostafa Tarkesh Esfahani, Saeid Pourmanafi, Norair Toomanian, Bahareh Aghasi, Ahmad Jalalian
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Digital soil mapping
Ensemble modeling
Spectral indices
Variable selection (Boruta)
Environmental covariates
Cross-validation
Online Access:https://doi.org/10.1038/s41598-025-04554-8
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https://doi.org/10.1038/s41598-025-04554-8

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