Identifying Road safety discrepancies and measuring spatial dependencies using cluster analysis

  • Charan Kumar G, G. Shobhalatha, K Rajyalakshmi

Abstract

Spatial analysis plays a key role in analyzing the information identified with graph theory in different areas with spatial aspects. Characterizing the spatial area of the substances is the crucial issue in the spatial graph theory. Representation of graphs and empirical relation between several objects are key role in analyzing the spatial graph theory.  In the present paper, we made an endeavor to comprehend the spatial graph properties and it very well may be utilized to portray, contrast just as with test explicit theory of road security measures concerning explicit areas. The integration of Graph theory, clustering analysis and spatial autocorrelation provides a scientific way for measuring the entities associated in road safety. Here we mainly focused on the affect of road safety by the impact of several road discrepancies in our selected area. Spatial dependencies for each discrepancy can be studied by the method of Moran’s I index and clustering analysis.

 KEYWORDS: Spatial graphs, spatial dependencies, Moran’s I index, clustering.

Published
2020-06-06
How to Cite
Charan Kumar G, G. Shobhalatha, K Rajyalakshmi. (2020). Identifying Road safety discrepancies and measuring spatial dependencies using cluster analysis. International Journal of Advanced Science and Technology, 29(05), 11154-11165. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/25206