Wednesday, November 15, 2006
286-1

Assessment of Fuzzy Clustering Analysis with Kriging in Delineating the Soil Management Zones.

Kai-Wei Juang1, Dar-Yuan Lee2, Wei-Ging Su3, and Ten-Lin Liu3. (1) Dept. Post-Modern Agri., MingDao Univ.,, 369 Wen-Hua Rd., Pitou,, Changhua County, 523, Taiwan, Republic of China, (2) National Taiwan University, Dept.of Agric. Chemistry, National Taiwan Univ., Taipei, TAIWAN, (3) Dept of Ag Chemistry, National Taiwan Univ, Taipei, Taiwan

Fuzzy clustering analysis (FCA) is increasingly used to delineate zones for site-specific management. Sampled observations of soil properties can be classified into groups by using FCA given a membership function. The boundaries of management zones are thus determined on the spatial distribution of grouped soils. In practice, the sampling density will not be intensive enough to determine the management zone boundaries precisely. Thus, a scheme of fuzzy clustering analysis combined with kriging technique, which used in spatial interpolation of soil properties, was proposed. However, there are few detailed discussions for assessing the feasibility of fuzzy clustering analysis combined with kriging to delineate management zones of agricultural soils. In this study, a comparison of two approaches of fuzzy clustering analysis combined with kriging, kriging membership values of fuzzy classification and putting kriged soil properties into fuzzy classification, was carried out. The study site was 20 ha in area in Changhua County, Taiwan. The observed data of pH, electronic conductivity (EC), and soil texture were used for illustration the performance of fuzzy classification and kriging interpolation. The results of classification showed that the soil texture-based management zones were with lower within-group variation but were not the pH- and EC-based management zones. The soil texture-based management zones were more robust than those pH- and EC-based. Moreover, compared with one of kriging membership values of fuzzy classification to determine management zones, the other of putting kriged soil properties into fuzzy classification got a lower misclassification rate. The approach of putting kriged soil properties into fuzzy classification was thus recommended in this study.