Artikel ; Online: Tree-based algorithms for spatial modeling of soil particle distribution in arid and semi-arid region.
Environmental monitoring and assessment
2024 Band 196, Heft 3, Seite(n) 264
Abstract: Accurate estimation of particle size distribution across a large area is crucial for proper soil management and conservation, ensuring compatibility with capabilities and enabling better selection and adaptation of precision agricultural techniques. The ... ...
| Abstract | Accurate estimation of particle size distribution across a large area is crucial for proper soil management and conservation, ensuring compatibility with capabilities and enabling better selection and adaptation of precision agricultural techniques. The study investigated the performance of tree-based models, ranging from simpler options like CART to sophisticated ones like XGBoost, in predicting soil texture over a wide geographic region. Models were constructed using remotely sensed plant and soil indexes as covariates. Variable selection employed the Boruta approach. Training and testing data for machine learning models consisted of particle size distribution results from 622 surface soil samples collected in southeastern Turkey. The XGBoost |
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| Mesh-Begriff(e) | Soil ; Clay ; Sand ; Environmental Monitoring/methods ; Algorithms | |||||
| Chemische Substanzen | Soil ; Clay (T1FAD4SS2M) ; Sand | |||||
| Sprache | Englisch | |||||
| Erscheinungsdatum | 2024-02-14 | |||||
| Erscheinungsland | Netherlands | |||||
| Dokumenttyp | Journal Article | |||||
| ZDB-ID | 782621-7 | |||||
| ISSN | 1573-2959 ; 0167-6369 | |||||
| ISSN (online) | 1573-2959 | |||||
| ISSN | 0167-6369 | |||||
| DOI | 10.1007/s10661-024-12431-6 | |||||
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| Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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