Hybridization of cokriging and gaussian process regression modelling techniques in mapping soil sulphur

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F21%3A85813" target="_blank" >RIV/60460709:41210/21:85813 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0341816221003921?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0341816221003921?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.catena.2021.105534" target="_blank" >10.1016/j.catena.2021.105534</a>

Result language
angličtina
Original language name
Hybridization of cokriging and gaussian process regression modelling techniques in mapping soil sulphur
Original language description
As a widely used soil mapping method, the kriging method involves a high sampling point to generate quality and accurate maps. Combining kriging and machine learning (ML) can produce soil maps with fewer number sampling points. This study objective was to implement a hybrid approach based on the Cokriging (Cok) and an ML technique, i.e., Gaussian process regression (GPR). The hybrid method called the Cok-GPR method uses the Cok as a predictor method of the soil sulphur and then uses GPR to improve the prediction accuracy. The proposed method was compared with the Cok and the GPR models, respectively, in a case study. Soil samples (115) were collected from the topsoil at the agricultural site of approximately 889,8 km2 size. S, Ca, K, Mg, Na, P, and V were estimated via Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). All the models were evaluated by MAE, RMSE and R2 criteria. The proposed Cok-GPR model can be applied to efficiently predict soil nutrient element levels at the region
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
40104 - Soil science

Project
<a href="/en/project/EF16_019%2F0000845" target="_blank" >EF16_019/0000845: Centre for investigation of synthesis and transformation of nutritional substances in the food chain in interaction with potentially harmful substances of athropogenic origin: assessment of contamination risks for the quality of production</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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