Urban green space distribution in Oklahoma City: A spatial analysis of bio-physical and socio-economic characteristics

Abstract

Oklahoma City, Oklahoma (OKC) is a fast-growing city undergoing urbanization. Rapid urbanization can lead to neighborhood construction where impervious surfaces are prioritized over urban green space (UGS). Urban green space can be defined as green vegetation on housing parcels not just parks and recreational areas. Housing properties are funded through banks and socio-economic status. Creating an efficient UGS without proper funding can make UGS unsustainable. Redline districts are districts that are financially hazardous to fund. National Agriculture Imagery Program (NAIP) offers high spatial resolution imagery (1m) that is used to create land cover classification map consisting of trees and grass in Google Earth Engine (GEE). Comparing percentage of trees (dependent) to socio-economic status variables and bio-physical variables told us that the spatial autocorrelation with a financially hazardous neighborhood exhibited higher tree percentages and higher Normalized Difference Vegetation Index (NDVI) in comparison to neighborhoods declared desirable. Financially hazardous neighborhoods do show a higher percentage of vacant lots which leads to overgrown vegetation. Overgrown vegetation will help the remote sensing camera detect a pure vegetation pixel compared to a sparse environment where the camera may detect the soil instead of vegetation. Much more research is still needed to bring down the number of variables that have an effect on vegetation growth.