Efficiency of interpolation methods based on GIS for estimating of spatial distribution of pH in soil
2019
Myslyva, T., Belarusian State Agricultural Academy, Gorki, Mogilev reg. (Belarus) | Kutsaeva, O., Belarusian State Agricultural Academy, Gorki, Mogilev reg. (Belarus) | Krundzikava, N., Belarusian State Agricultural Academy, Gorki, Mogilev reg. (Belarus)
The main objective of this study is to review and evaluate three common interpolation methods namely: Inverse Distance Weighting (IDW), Radial Basis Function (RBF) and Ordinary Kriging (OK), and generate maps of soil pH using these methods. The accuracy and efficiency of the generated maps have been examined as well as the most fitting technique for estimating spatial distribution of soil pH in the study area is identified. Studies were conducted within the limits of land use of RUP “Uchkhoz BGSHA” (Republic of Belarus, Mogilev region, Goretsky district). The total area of the surveyed territory is 3197.89 hectares. For the analysis data is used about pHKCl of soil solution obtained from materials of an agrochemical survey executed in 2014. Forecasting and visualization of the spatial distribution of pH sub(KCl) was carried out using the Geostatistical Analyst module of the ArcGIS software. The experimental anisotropic variograms were calculated to determine the possible spatial structure of soil pH. Based on cross-validation results, a polynomial function was identified as the best variogram model. The model created by the method of radial basis functions turned out to be the most suitable for forecasting purposes (the value of the root-mean-square error was 0.763). In terms of interpolation accuracy, the investigated deterministic and geostatistical methods are located in the next descending row: RBF greater than IDW greater than OK.
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