Comparison of kriging interpolation precision between grid sampling scheme and simple random sampling scheme for precision agriculture

Year 2016, Volume: 5 Issue: 1, 62 - 73, 02.01.2016

Jiang Houlong Wang Daibin Xu Chen Liu Shuduan Wang Hongfeng Yang Chao Li Najia Chen Yiyin Geng Lina

https://doi.org/10.18393/ejss.2016.1.062-073

Cited By: 5

Abstract

Sampling methods are important factors that can potentially limit the accuracy of predictions of spatial distribution patterns. A 10 ha tobacco-planted field was selected to compared the accuracy in predicting the spatial distribution of soil properties by using ordinary kriging and cross validation methods between grid sampling and simple random sampling scheme (SRS). To achieve this objective, we collected soil samples from the topsoil (0-20 cm) in March 2012. Sample numbers of grid sampling and SRS were both 115 points each. Accuracies of spatial interpolation using the two sampling schemes were then evaluated based on validation samples (36 points) and deviations of the estimates. The results suggested that soil pH and nitrate-N (NO₃-N) had low variation, whereas all other soil properties exhibited medium variation. Soil pH, organic matter (OM), total nitrogen (TN), cation exchange capacity (CEC), total phosphorus (TP) and available phosphorus (AP) matched the spherical model, whereas the remaining variables fit an exponential model with both sampling methods. The interpolation error of soil pH, TP, and AP was the lowest in SRS. The errors of interpolation for OM, CEC, TN, available potassium (AK) and total potassium (TK) were the lowest for grid sampling. The interpolation precisions of the soil NO₃-N showed no significant differences between the two sampling schemes. Considering our data on interpolation precision and the importance of minerals for cultivation of flue-cured tobacco, the grid-sampling scheme should be used in tobacco-planted fields to determine the spatial distribution of soil properties. The grid-sampling method can be applied in a practical and cost-effective manner to facilitate soil sampling in tobacco-planted field.

Keywords

Grid sampling scheme, Interpolation precision, simple random sampling scheme, precision agriculture

References

• Bremner, J.M., Mulvaney, C.S., 1984. Total nitrogen In: Methods of Soil Analysis, page, A.L. (ED.). 2nd Edn. Agron. No. 9, Part 2: Chemical and microbiological properties. Am. Soc. Argon. Madison, WI. USA. pp. 595-624.
• Brus, D.J., de Gruijter, I.J., van Groenigen, J.W., 2006. Designing spatial coverage samples using the k-means clustering algorithm. In: Digital Soil Mapping: An Introductory Perspective. P. Lagachene, A. B. McBratney, M. Voltz (eds.). Elsevier, Amsterdam, Netherlands.
• Caeiro, S., Goovaerts, P., Painho, M., Costa, H., Sousa, S., 2002. Optimal spatial sampling design for mapping estuarine sediment management areas. AGILE Conference on Geographic Information Science, Palma, p. 1-6.
• Cahn, M.D., Hummel, J.W., Brouer, B.H., 1994. Spatial analysis of soil fertility for site-specific crop management. Soil Science Society America Journal 58: 1240-1248.
• Cambardella, C.A., Moorman, T.B., Parkin, T.B., Karlen, D.L., Novak, J.M., Truko, R.F., Konopka, A.E., 1994. Field-scale variability of soil properties in central Iowa soils. Soil Science Society America Journal 58: 1501-1511.
• Chapman, H.D., 1965. Cation exchange capacity. In: methods of soil analysis, black, C.A. (ED.). Part 2. Number 9 in the series agronomy: American institute agronomy, Madison, Wisconsin. pp. 891-901.
• Christman, M.C., 2000., A review of quadrat-based sampling of rare geographically clustered populations. Journal of Agricultural Biological and Environmental Statistics 5: 168–201.
• Ferguson, R.B., Hergert, G.W., Schepers, J.S., Gotway, C.A., Cahoon, J.E., Peterson, T.A., 2002. Site-specific nitrogen management of irrigated maize: Yield and soil residual nitrate effects. Soil Science Society America Journal 66: 544-553.
• Frogbrook, Z.L., 1999. The effect of sampling intensity on the reliability of predictions and maps of soil properties. In: Proceedings of the 2nd European Conference on Precision Agriculture. Sheffield Academic Press, Sheffield, UK. pp. 71-80.
• Goovaerts, P., 1998. Geostatistical tools for characterizing the spatial variability of microbiological and physicochemical soil properties. Biology and Fertility of Soils 27: 315-334.
• Goovaerts, P., 2000. Estimation or simulation of soil properties? An optimization problem with conflicting criteria. Geoderma 97: 165-186.
• Gotway, C.A., Ferguson, R.B., Hergert, G.W., Peterson, T.A., 1996. Comparison of kriging and inverse-distance methods for mapping soil parameters. Soil Science Society America Journal 60: 1237-1247.
• Gupta, R.K., Mostaghimi, S., McClellan, P.W., Birch, J.B., Brann, D.E. 1999. Modeling spatial variability of soil chemical parameters for site-specific farming using stochastic. Water Air and Soil Pollution 110: 17–34.
• Haining, R. 1990. Spatial data analysis in the social and environmental sciences. Cambridge University Press. 409 pp.
• Issaks, E., Srivastava, R.M. 1989. An Introduction to Applied Geostatistics. Oxford University Press, New York.
• Jiang H.L., Liu G.S., Wang X.Z., Song, W.F., Zhang, R.N., Zhang, C.H., Hu, H.C., Li, Y.T., 2010. Spatial variability of soil properties in a long-term tobacco plantation in central China. Soil Science 175: 137-144.
• Jiang H.L., Liu G.S., Wang, R., Liu, S.D., Han, F.G., Yang, Y.F., Ye, X.F., Zhang, Q.J., Wang, X.J., Wang, Z.H., Hu, H.C., 2011. Delineating site-specific quality-based management zones for a tobacco field. Soil Science 176: 206-212.
• Johnston, K., Hoef, J.M.V., Krivoruchko, K., Lucas. N., 2001. Using ArcGIS Geostatistical Analysis. GIS User Manual by ESRI, New York.
• Kumar, N. 2009. An optimal spatial sampling design for intra-urban population exposure assessment. Atmospheric Environment 43: 1153–1155.
• Li, Q.Q., Wang, C.Q., Yue, T.X., Li, B., Yang, J., Shi, W.J., 2008. Error analysis of soil property spatial interpolation with RBF artificial neural network with different input methods. Acta Pedologica Sinica 459: 360-365.
• Li, Y., Shi, Z., Wu, C.F., Li, F., Li, H.Y., 2007. Optimised spatial sampling scheme for soil electriclal conductivity based on Variance Quad-Tree (VQT) method. Agricultural Sciences in China 6: 1463-1471.
• Lindsley, C. M., Bauer, F. C. 1929. Test your soil for acidity. University of Illinosis, College of Agriculture and Agricultural Experiment Station, Circular No. 346. USA.
• Liu, G.S., 2003. Tobacco Cultivation. China Agricultural Press, Beijing, China. (In Chinese)
• Liu, G.S., Wang, X.Z., Zhang, Z.Y., Zhang, C.H., 2008. Spatial variability of soil properties in a tobacco field of central China. Soil Science 173: 659-667.