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Showing 1 results for Hierarchical Clustering Analysis

H. Ghamarnia, F. Sasani, B. Yargholi,
Volume 23, Issue 1 (6-2019)
Abstract

Exploring the homogenous regions for site specific management is important, especially in the areas under different anthropogenic activities. This was investigated using multi-way analysis including Factor Analysis, Hierarchical Clustering Analysis and k means in the areas under long-term wastewater irrigation over a period of more than 40 years, in Shahre Rey, south of Tehran. By using Factor Analysis model, eight factors as eight geochemical groups were extracted to explain approximately 60% of the total variance related to 37 soil physicochemical properties. The most important groups included the nutrient elements (OM, OC and N), micronutrients (Mn and B), soil water adsorption capacity (Clay, Silt, Sand and CEC), salinity and osmotic pressure (EC, OP and TDS) and sodification (SAR and Na). The maximum values of Cophenet and Silhouette coefficients were equal to 0.77 and 0.83, respectively, dictating the selection of the average linkage approach in Hierarchical Clustering Analysis and three clusters in the k-average method with 19, 24 and 34 mapping units. The Thiessen Polygons method in GIS was applied to separate the geochemical groups in the form of mapping units. This output, which was, in fact, the combination of multi-way models and its visual representation in GIS under separated mapping units of study area, could present suitable management activities for the areas under each cluster.


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