Exploring the Spatial Correlation of Blight and Litter: A Case Analysis of Memphis, Tennessee Neighborhoods

Reza Banai () and Navid Enayati Shabkolaei
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Reza Banai: Department of City and Regional Planning, University of Memphis, Memphis, TN 38152, USA
Navid Enayati Shabkolaei: Department of Civil, Construction, and Environmental Engineering, University of Memphis, Memphis, TN 38152, USA

Land, 2025, vol. 14, issue 9, 1-27

Abstract: Urban blight and litter are twin issues that significantly affect the quality of life in city neighborhoods. This paper investigates the relationship between blight and litter, commonly overlooked in urban studies literature. We measure the prevalence of blight and litter across block groups in our mapping with a focus on socioeconomic factors, including income levels, crime rates, and land use types (industrial, commercial, and residential) for our case study, Memphis, Tennessee. Using statistical and spatial analytics, as well as data from the Memphis Data Hub and the City of Memphis, we show the prevalence of blight and litter across block groups. GIS was used to map neighborhood-specific blighted structures and their spatial connection to litter accumulation. We also explore the distribution of blight and litter across different land uses. A Pearson correlation value of 0.639 suggests a strong positive relationship between blight and litter at the block group level. Spatial clustering is assessed by Global Moran’s I and Local Moran’s I, identifying neighborhood-level hotspots. The block group is used as the unit of analysis to capture micro-spatial variation and to enable meaningful equity-based insights at the neighborhood level. Our mapping offers practical insights into urban revitalization strategies in deference to per capita income, crime rate, and land use. The findings contribute to urban policy discussions by promoting the joint consideration of blight and litter, helping guide future community-based interventions aimed at alleviating the negative impacts of blight and litter, particularly in disadvantaged neighborhoods.

Keywords: blight; litter; socio-spatial indicators; spatial autocorrelation (Moran); block groups; neighborhoods; GIS (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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