Grouping of Land Use Data-based Mapping Clusters’ Techniques in The Case of Muang Nakhonratchasima District, Thailand
DOI:
https://doi.org/10.14456/jiskku.2021.19Keywords:
Land use, Spatial clustering analysis, Technique of cluster and outlier analysis, Technique of hot spot analysisAbstract
Purpose of the study: The objective of this study is to group statistical significantly the land using grouping technique for mapping cluster technique in Muang Nakhonratchasima District.
Methodology: The investigation focuses on the land use grouping using two techniques for cluster mapping in ArcMap program: 1) Cluster and Outlier Analysis (Anselin Local Moran’s) and 2) hot spot analysis (Getis-Ord-Gi)
Main findings: The findings reveal that the cluster analysis is appropriate for grouping urban and housing areas while the outlier analysis is good for agricultural and dwelling ground. Only contiguity edges and corners with Euclidian distance are recommended for clustering since it can group as many large areas as possible. Furthermore, hot spot analysis is suitable at various confidence levels for examining urban and dwelling areas and agricultural lands. Inverse distance (square)-based Euclidian and Manhattan distance is suggested for hot spot clustering at high confidence level because it can group as many areas as possible at the greatest confidence level too.
Applications of the study: Findings of this study can be utilized for the spatio-temporal analysis and land use planning of the city of Nakhornratchasima to enable the land use operation more systematically and at the maximum benefit to the public.
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References
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