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Article ; Online: Tree-based algorithms for spatial modeling of soil particle distribution in arid and semi-arid region.

Abakay, Osman / Kılıç, Miraç / Günal, Hikmet / Kılıç, Orhan Mete

Environmental monitoring and assessment

2024  Volume 196, Issue 3, Page(s) 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
MeSH term(s) Soil ; Clay ; Sand ; Environmental Monitoring/methods ; Algorithms
Chemical Substances Soil ; Clay (T1FAD4SS2M) ; Sand
Language English
Publishing date 2024-02-14
Publishing country Netherlands
Document type 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
Shelf mark
Z 5186: Show issues
Database MEDical Literature Analysis and Retrieval System OnLINE

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