Evaluation of conditioned latin hypercube sampling as a support for soil mapping and spatial variability of soil properties

Abstract

In soil surveys, the number of collected samples is commonly reduced by factors that hamper field activities, such as rugged terrain and lack of roads. Conditioned Latin hypercube (CLH) sampling has been used to properly capture soil variability across the landscape, whereas cost-constrained conditioned Latin hypercube (CCLH) sampling limits the sampling to areas of easy access. The objectives of this work were to: (i) compare the efficiency of CLH and CCLH sampling systems to create soil maps, considering the number of soil classes covered per system, (ii) compare both systems to map soil A horizon thickness, and (iii) generate a detailed soil map of the study area to assist in decision makings. The study was performed in Minas Gerais, Brazil. A digital elevation model (DEM) and its terrain derivatives were the basis for CLH and CCLH to determine the sampling points. The CCLH system also required a cost map that represented the difficulty of reaching every place in the area. At the sampling locations, soil information was observed, allowing for the creation of those maps that were further validated in the field. Kappa index, global index (GI), RMSE, 1:1 ratio graphic, and R2 were the comparison parameters. Conditioned Latin hypercube presented higher accuracy than CCLH to represent both soil classes and soil attributes, although the samples were spread out in the area. Cost-constrained conditioned Latin hypercube was less representative than CLH, but it may contribute to soil sampling in areas of difficult access, common in developing countries, such as Brazil.