Infrastructure inequality is a characteristic of urbanization

Abstract

Urbanization can challenge sustainable development if it produces unequal outcomes. Infrastructure is an important urbanization dimension, providing services to support diverse urban activities. However, it can lock in unequal outcomes due to its durable nature. This paper studies inequalities in infrastructure distributions to derive insights into the structure and characteristics of unequal outcomes associated with urbanization. We analyzed infrastructure inequalities in two emerging economies in the Global South: India and South Africa. We developed and applied an inequality measure to understand the structure of inequality in infrastructure provisioning (based on census data) and infrastructure availability (based on satellite nighttime lights [NTLs] data). Consistent with differences in economic inequality, results show greater inequalities in South Africa than in India and greater urban inequalities than rural inequalities. Nevertheless, inequalities in urban infrastructure provisioning and infrastructure availability increase from finer to coarser spatial scales. NTL-based inequality measurements additionally show that inequalities are more concentrated at coarse spatial scales in India than in South Africa. Finally, results show that urban inequalities in infrastructure provisioning covary with urbanization levels conceptualized as a multidimensional phenomenon, including demographic, economic, and infrastructural dimensions. Similarly, inequalities in urban infrastructure availability increase monotonically with infrastructure development levels and urban population size. Together, these findings underscore infrastructure inequalities as a feature of urbanization and suggest that understanding urban inequalities requires applying an inequality lens to urbanization.

Keywords: developing countries; spatial scale; sustainability; urban inequality; urbanization.

Fig. 1.

(A) Multidimensional urbanization and multiscalar inequalities. (B) Deriving inequality levels from first- (μ) and second- (σ) order moments of infrastructure distributions constrained by an upper bound (0 < μ < 1). The figure shows three typologies of changes in infrastructure distributions: no inequality (I = 0), maximum inequality (I = 1), and intermediate inequality (0 < I < 1).

Fig. 2.

Inequalities in infrastructure provisioning. (A) Inequality levels ($I_1$) based on infrastructure-provisioning index ($IP$) (Left) and average infrastructure provisioning index ($I{P}_{\mu }$) (Right) estimates in South Africa and India classified by urban (u) and rural (r) areas. (B) Urban inequality based on infrastructure provisioning index in India (district, $I_{3u}$) and South Africa (municipality, $I_{4u}$). (C) Urban inequality ($I_{su}$) across scales (s) in India and South Africa. Whiskers represent ±1.75 times the interquartile range. (D) Inequality ($I_{5u}$) levels across cities in India and South Africa.

Fig. 3.

Inequalities in infrastructure availability. (A) Comparing South Africa and India based on inequality estimates from VIIRS NTLs across administrative scales (Top) and lattice grids with resolutions varying from 0.05° to 1° (Bottom). Level 1 corresponds to provinces (South Africa) and states (India), level 2 corresponds to districts, and level 3 corresponds to municipalities (South Africa) and subdistricts (India). (B) Comparing inequality levels across urban areas in India and South Africa with varying NTL thresholds. (C) Comparing rate (β) of change in inequality levels across spatial scales (based on lattice grid resolutions) between India and South Africa. Higher (lower) β implies more (less) concentrated inequality at coarse spatial scales.

Fig. 4.

(log) Inequality levels measured from NTL images as a function of (log) mean NTLs in India and South Africa evaluated at a spatial scale of 0.25° (lattice grid resolution) and with an NTL upper bound of 50 nWsr⁻¹cm⁻².