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Social disparities in tree canopy and park accessibility: A case study of six cities in Illinois using GIS and remote sensing
Authors:Xiaolu Zhou  Jinki Kim
Institution:1. Rubenstein School of Environment and Natural Resources, Transportation Research Center, University of Vermont, 81 Carrigan Drive, Burlington, VT 05405, United States;2. Department of Geography, University of South Carolina, Callcott Building, 709 Bull Street, Columbia, SC 29208, United States;3. College of Engineering and Mathematical Sciences, Transportation Research Center, University of Vermont, Farrell Hall, 210 Colchester Avenue, Burlington, VT 05405, United States;4. Rubenstein School of Environment and Natural Resources, University of Vermont, 81 Carrigan Drive, Burlington, VT 05405, United States
Abstract:Easy access to green space and the presence of lush tree canopy in neighborhoods provide substantial psychophysical benefits to residents. However, these urban amenities are often unevenly distributed between white and racial/ethnic minority residents. In this study, we investigated racial/ethnic disparities in access to parks and tree canopy using a geographic information system (GIS) and remote-sensing techniques in six Illinois cities. An accessibility index based on a new Google Maps application programming interface (API) was used to calculate walking distances between points of origins and parks, and integrated classification techniques were applied to calculate the amount of tree canopy. Kernel-smoothing function was applied to both canopy and park layers to transform point value to continuous surface value. Both ordinary regression and spatial regression were used to find the relationship.The results of this study show that racial/ethnic minorities have less tree canopy in their neighborhoods, but it did not find significant differences in terms of access to parks. Spatial regression was determined to be an effective modeling approach for the data used in this study. Methods used in this study can be extended to study accessibility to various destinations using different means of transit, and the results can guide intervention programs to help reduce environmental inequity.
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