M. Nourzadeh, S. M. Hashemy, M. J. Malakouti,
Volume 15, Issue 57 (10-2011)
Abstract
Electrical conductivity and acidity of soil are the most important chemical factors of soil for agriculture. The nature of soil is in such a way that its change has a continuous form. The method that can take into account this continuity will be able to show a better picture of change in soil characteristics. Objectives of this research are to investigate the relations between measured electrical conductivity and soil acidity of Qom plain, and clustering, compare the clustering methods, determine the optimum numbers of cluster, and to zone the clusters in the study area. Accordingly, two fuzzy clustering methods FCM and GK, were used for data mining and clustering of 465 measured data. For estimating the appropriateness and comparison of two methods, some criteria including Partition Coefficient, Classification Entropy, Partition Index, Separation Index and Xie and Beni's Index were used. Data mining results showed that the optimum number of clusters for FCM and GK method was 15 and 17, respectively. After investigating the results of clustering and based on the criteria of appropriateness, it was indicated that GK was the best clustering method. According to this method, 295 data from 465 measured samples had more than 40 percent of membership function. So, 9 clusters from 17 clusters had more than 20 members. Then salinity-alkalinity zoning based on GK method to show the clusters distribution better in the study area was prepared. This prepared fuzzy map explained that most of Northwest and west belonged to cluster 1 and eastern parts of study area include belonged to cluster 17. Based on this, salinity-alkalinity and the ensuing soil degradation in east of study area is more likely than the west of it.
