A fine-grained, versatile index of remoteness to characterize place-level rurality

TL;DR

This paper introduces a new, fine-grained remoteness index for places that captures within-county rurality variations and is consistent over time, aiding long-term rural-urban studies.

Contribution

It presents a distance-based, place-level remoteness index using population data, improving upon county-level classifications for detailed and temporal analyses.

Findings

Index captures within-county rurality variations.

Applicable to data-scarce environments and historical periods.

Enables consistent long-term rural-urban analysis.

Abstract

Rural-urban classifications are essential for analyzing geographic, demographic, environmental, or socioeconomic processes across the rural-urban continuum. However, existing county-level classifications may ignore the within-county variations of rurality, which can be problematic if the scale of interest is at the place-level or finer. Moreover, existing rural-urban classification are often inconsistent over time and thus, impede the long-term analysis of rural-urban dynamics. We developed a distance-based method to generate place-level remoteness estimates based on simple input data. We create our remoteness index based on place-level population data for the U.S. from 1980 to 2010. The proposed index is generalizable to data-scarce environments and earlier time periods and is based on the distances of a given place to the nearest places of different population sizes, and allows for fine-grained, temporally consistent analyses of rural-urban processes.