Computer-assisted mapping of paddy-field soils

Abstract

In order to determine how a conventional soil map on a local scale can be reproduced from soil sample information, a set of numerical procedures was applied to the soil chemical data from 159 soil samples collected in paddy fields of the Aizu Basin, in the northern part of Japan. The digital elevation data were also included as an attribute.

Various steps were involved. In the first step, the sparse data were converted into a closely spaced data set. This first step was previously described in Part I of this paper. In the second step a multivariate ordination (principal component analysis) was applied to the sampling data in order to avoid redundancy of information. Large contributions to the first component were derived from the values of CEC and exchangeable Ca and Mg. In the third step the sampling sites were numerically classified using the results of four or five components obtained in the second step. A hierarchical clustering method was applied to provide the initial set of clusters for non-hierarchical clustering. In the fourth step the closely spaced data collected in the first step were allocated to an appropriate class obtained by using the non-hierarchical clustering method applied in the third step. For the allocation method, the geographic location of the sampling sites was included as an additional characteristic of the data.

In the regional partition map based on the numerical procedures, each soil group corresponded to a soil series in the original conventional soil map which depended predominantly on detailed morphological and topographical differences. In addition, the regional partition map was found to provide useful information for the identification of factors closely related to soil fertility, by statistically examining the differences in rice yield among the soil groups.

Key Words:

• numerical classification
• paddy soils
• rice production
• soil mapping