The use of legacy soil data for digital soil mapping is determined by the type of data available. When soil profile data is available, it can be used as inputs to predict soil properties at unsampled locations (McBratney et al., 2003). This dataset contains two types of data (i) Data Set A which consists of 76 georeferenced locations for which A and B horizons were sampled. Composite samples of the A horizon were collected between depths of 0 – 30 cm for fertility analysis, while the B horizon was sampled to an unspecified depth. (ii) Data Set B consists of detailed soil profile pit descriptions and analytical data for 48 georeferenced profiles presumably from pits. To make Data Set B comparable with Data Set A, an equal area quadratic smoothing spline function (Ponce-Hernandez et al., 1986; Bishop et al., 1999; Malone et al., 2009) in the ithir package in R statistical software (Malone, 2017) was used to predict soil attributes for Data Set B over the interval of 0 – 30 cm. This data set was used to determine whether existing legacy soil data for a selected potion of Kenya could be used to quantitatively predict soil properties at a higher spatial resolution than current maps by using DSM techniques without conducting additional field work. Data Set A was used as the calibration dataset whereas Data Set B was used as the evaluation dataset.
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Malone, B. P., McBratney, A. B., Minasny, B., & Laslett, G. M. (2009). Mapping continuous depth functions of soil carbon storage and available water capacity. Geoderma, 154:138-152.
McBratney, A. B. (1998). Some considerations on methods for spatially aggregating and disaggregating soil information. Nutrient Cycling in Agroecosystems, 50:51-62.
McBratney, A. B., Santos, M. M., & Minasny, B. (2003). On digital soil mapping. Geoderma, 117:3-52.
Ponce‐Hernandez, R., Marriott, F. H. C., & Beckett, P. H. T. (1986). An improved method for reconstructing a soil profile from analyses of a small number of samples. European Journal of Soil Science, 37:455-467.
Cite this work
Researchers should cite this work as follows:
- Minai, J. O., Schulze, D. G. (2019). Soil Property Data for Spatial Prediction of Soil Properties for the Busia Area, Kenya. Purdue University Research Repository. doi:10.4231/00R1-HM25