Spatial Interactions: Evaluation with the Help of Global and Local Moran’s Index

Abstract

In the present work, the authors demonstrate the possibility of using Moran’s index and its components on the example of Samara region. As area units the study employs 37 municipalities of the 1st level - 10 urban districts and 27 municipal townships. Using the global Moran’s index the researchers construct a spatial scatter plot and reveal four territorial clusters: kernels, the satellite-counterbalance, the periphery and areas outside the influence of kernels and the satellite-counterbalance. Next, using the local Moran’s index the authors determine six sub clusters: kernels, the satellite-counterbalance, the area of profound effect of kernels and the satellite-counterbalance, the area of low impact of kernels and the satellite-counterbalance, the kernels’ counterweight and areas outside the influence of kernels and the satellite-counterbalance. The local Moran’s index decomposition helps to identify areas of influence of both the Samara city kernel and the integrated system of Samara and Tolyatt

Keywords

• spatial autocorrelation
• global Moran’s index
• local Moran’s index
• cluster
• Samara region