Selection of a Geostatistical Method to Interpolate Soil Properties of the State Crop Testing Fields using Attributes of a Digital Terrain Model
| Autor: | S. S. Ryazanov, T. G. Kolcova, I. A. Sahabiev, B. R. Grigoryan |
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| Rok vydání: | 2018 |
| Předmět: |
Soil map
Soil Science 04 agricultural and veterinary sciences 010501 environmental sciences 01 natural sciences Kriging Multicollinearity Statistics Linear regression 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Principal component regression Spatial dependence Variogram 0105 earth and related environmental sciences Earth-Surface Processes Interpolation Mathematics |
| Zdroj: | Eurasian Soil Science. 51:255-267 |
| ISSN: | 1556-195X 1064-2293 |
| Popis: | The three most common techniques to interpolate soil properties at a field scale—ordinary kriging (OK), regression kriging with multiple linear regression drift model (RK + MLR), and regression kriging with principal component regression drift model (RK + PCR)—were examined. The results of the performed study were compiled into an algorithm of choosing the most appropriate soil mapping technique. Relief attributes were used as the auxiliary variables. When spatial dependence of a target variable was strong, the OK method showed more accurate interpolation results, and the inclusion of the auxiliary data resulted in an insignificant improvement in prediction accuracy. According to the algorithm, the RK + PCR method effectively eliminates multicollinearity of explanatory variables. However, if the number of predictors is less than ten, the probability of multicollinearity is reduced, and application of the PCR becomes irrational. In that case, the multiple linear regression should be used instead. |
| Databáze: | OpenAIRE |
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