Urban greenspace linked to lower crime risk across 301 major U.S. cities

Scott Ogletree, Lincoln Larson, Robert B. Powell, David L. White, Matthew T.J. Brownlee

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Greenspace enhances quality of life for urban residents in many ways, but it may also produce unexpected and undesired consequences. For example, a growing literature is exploring the relationship between greenspace and crime in cities, yielding mixed results. To address this question on a larger scale across diverse contexts, we used a multilevel modeling approach to investigate the relationship between different types of crime and urban greenspace in 59,703 census block groups within the 301 largest cities in the United States. After accounting for potential covariates of crime, including demographic, socioeconomic, and climate variables, we found that, on average, census block groups with more greenspace (measured by NDVI) had lower risk of both property (β = −0.66 [−0.70 to −0.61]) and violent crime (β = −0.25 [−0.28 to −0.22]). For property crime, this significant negative relationship held for all but one city in the sample (Cape Coral, FL), and no cities displayed a significant positive relationship. For violent crime a negative relationship was found for 289 cities and only three cities displayed a significant positive relationship (Chicago, IL, Detroit, MI, and Newark, NJ). Further research could strive to investigate the mechanisms fueling these significant and consistent trends and explore relationships between different types of crime and specific components and seasonal variations of greenspace.
Original languageEnglish
Article number103949
Pages (from-to)1-12
Number of pages12
Publication statusPublished - 24 Aug 2022

Keywords / Materials (for Non-textual outputs)

  • crime
  • urban greenspace
  • multilevel model


Dive into the research topics of 'Urban greenspace linked to lower crime risk across 301 major U.S. cities'. Together they form a unique fingerprint.

Cite this