Assessing urban vegetation inequalities: Methodological insights and evidence

Abstract

Vegetation indixes have become increasingly popular in analyzing urban inequalities in access to and use of green spaces. However, the methodologies employed have been heterogeneous, leading to inconclusive or contradictory results. This study aims to conduct a scoping literature review of research that evaluates methodologies used to estimate the inequal distribution of vegetation in cities, providing evidence to establish standardized guidelines for the selection of data sources, methodologies and indicators. The review includes 66 articles published between 2004 and 2023 from various global regions. We identified 10 vegetation indixes, with the Normalized Difference Vegetation Index (NDVI) being the most frequently used, typically derived from Landsat satellite data. The review highlights the importance of image acquisition times and temporal resolution in capturing dynamic urban environments. The spatial scale most adopted is the census block group, suitable for assessing urban inequalities. We observed substantial heterogeneity in the methodologies and statistical tools employed, with spatial autocorrelation analysis being the most common, followed by Pearson's and Spearman's correlation coefficients. ArcGIS was the most widely used GIS platform, closely followed by the cloud-based geospatial analysis platform Google Earth Engine, while R-Studio and Statistical Package for the Social Sciences (SPSS) were popular for statistical analysis. This study underscores the need for standardized methodologies to enhance the comparability and reliability of research on urban vegetation inequalities.