A new indicator of rural development based on fractal dimension and spatial accessibility

Keywords: Development, Fractal Dimension, Central place theory, spatial accessibility, Rural Geography
Session Type: Virtual Poster Abstract
Day: Sunday
Session Start / End Time: 2/27/2022 02:00 PM (Eastern Time (US & Canada)) - 2/27/2022 03:20 PM (Eastern Time (US & Canada))
Room: Virtual 38

Abstract

We aim to create a measure of the level of rural (under-)development by its (in)accessibility to goods, services, and opportunities. In central place theory, such accessibility is provided through the hierarchically nested structure of rural centers and towns. Based on the close relationships between the central place theory, the rank-size rule, and the fractal patterns, we set our objective of this paper is to test whether fractal dimensions of population distribution can be an indicator of rural development. This study uses the gridded population data because it is fractal. Our research area is the USA, and its congressional districts will be our basic unit of analysis. The fractal dimension is calculated for each district’s gridded population data in the USA by differential box-counting method for image analysis. Accessibility measures are computed for grocery stores and hospitals for each district by the gravity type negative exponential method with the impedance parameters given in Kwan, M. P. (1998). The results are explained with the help of a regression model. The results align with our hypothesis. Our results showed that the cities with high spatial accessibility tend to have high fractal dimension values and vice-versa. This model can predict the spatial accessibility to groceries stores and hospitals with a goodness of fit “67.5%”.