Urban green space is widely regarded as a valuable resource and a key part to a healthy and sustainable city, yet there are large disparities in the distribution of and access to green space, which reflect already existing income and socio-economic disparities. Using green space data and census data, this study assesses the impact of green space on gentrification in Washington, D.C., both spatially and temporally. Via GIS, descriptive statistics and spatial regression as the methods of analysis, the study's primary conclusion is that the change in non-Hispanic Black population is the most statistically significant predictor of distance to green space. Of all the models, using a multivariate model with distance to green space as the outcome variable is the most noteworthy and compelling model because it controls for other sociodemographic variables and is conducive to a lucid interpretation. The results show an eastward movement of green gentrification over the study period of 1990-2015. Furthermore, examining how GIS can be used to quantify gentrification induced by green spaces reveals considerable limitations, both with data availability and contextual factors. Suggested future research attempts to remedy some of these limitations by classifying green spaces by usage, using alternative data sources as proxies for gentrification, and delving into qualitative research.