Predicting soil properties over a region using sample information from a mapped reference area and digital elevation data: a conditional probability approach

In a previous paper [Voltz, hi., Lagacherie, P., Louchart, X., 1997, Predic ting soil properties over a region using sample information from a mapped r eference area. Fur. J. Soil Sci. 48, 19-30] a method for mapping soil prope rties with acceptable precision and cost was proposed. It combined soil cla ssification and interpolation by kriging, and used sample information from a reference area and simple soil observations over the mapping region. In t his paper a new version of the method was developed in which soil patterns are modelled by a conditional probability approach and are used to improve interpolation. The mapping method consists of three stages. First is the cl assification of a set of sites covering the region according to the soil cl assification of the reference area. Second is the determination over the re ference area of the probability of occurrence of soil classes at a site fro m the knowledge of the relief and of the soil classes at neighbouring sites . Third is the prediction of the soil properties at unvisited sites by a we ighted average of the values of the soil properties at the representative p rofiles of the soil classes, with the weights being taken proportional to t he conditional probability of occurrence of each soil class. The performanc e of the procedure was evaluated for mapping water content at wilting point in an area of 1736 ha in a physiographic region of Southern France. The me thod was compared with its previous version, namely classification with kri ging, and with ordinary kriging and prediction from a soil map at a scale o f 1:100 000. It was clearly more precise than the predictions from the 1:10 0 000 soil map and close to that of ordinary kriging with measured data. It performed similarly to classification with kriging when prediction points were close to observation points, but provided better results than classifi cation with kriging when prediction points were far from the observation po ints. This latter result illustrates the benefits of modelling soil pattern s as related to topographical features for interpolation purposes. (C) 2000 Elsevier Science B.V. All rights reserved.