The first step was conducting qualitative research by coding and mapping 25 different popular and scientific publications concerning urban green spaces. This gave a comprehensive look at the modern trends and big questions being asked in the field. To code these publications, we collected their data into an excel sheet including the place where the authors and scholars situated their analysis and research, which was then mapped into ArcGIS, juxtaposed with another layer that coded countries by the Human Development Index. This helps visualization of where the conversation surrounding green spaces is relevant and being talked about in either academic or popular media setting as well as a contextualization of those conversations and their relative country’s infrastructural development. This provided us with the background knowledge to help us define our focus question and methodology.
Urban green spaces are quite abundant in the Portland metropolitan area. So to better visualize some of the information we have collected on green spaces in Portland, we mapped each neighborhood’s proximity to green spaces in ArcGIS, coding neighborhoods from 1 to 5 on a relative scale, 1 being far away from green spaces, indicated in a dark green color and 5 being close to green spaces, indicated by a light green color. Another ArcGIS map we created described the demographics of these neighborhoods with the data on proximity to green spaces. Because Portland has an ongoing history with gentrification, we decided to map the population density of African American populations in Portland neighborhoods with the aforementioned proximity to green spaces. This map was helpful in visualizing who inhabits these neighborhoods. Although we saw clustering of these demographics within mostly dark green spaces, it is hard to theorize anything from this data because the dark green spaces made up much of the generally denser populated areas, so it would only make sense to see more of a certain population there. Our last general ArcGIS map we created contained data on urban sprawl with the green spaces in Portland. Using information from the urban sprawl index, which describes the uncontrolled urban growth of a population, categorizes neighborhoods by how fast it grows. In our map, the faster growing neighborhoods are coded in a light pink, while their slower growing counterparts, which generally described compacted city areas, are coded in a dark red. Then, our data on Portland neighborhoods’ proximity to green spaces overlaid with various sizes of green circles. From this map, we saw general growth in the more steadily growing urban areas, so there could be a correlation between the existence of green spaces in growing urban areas.
To first express the growth of these green spaces over time, in comparison to the grey spaces of places like neighborhoods and city centers, we used statistical data from Portland censuses dating back from 1980 and 2010. First, we examined individual population density of Portland neighborhoods during those two years. We applied this data to create a map in ArcGIS to visually show the growth of population over time as one layer. Next we found data that coded these neighborhoods by their relative access to green spaces. This helped us draw connections between how much urban sprawl has affected certain places and what the distribution of green spaces reflects on or from these changes. Because we knew correlation is not causation, we decided to run statistical tests on these data, specifically descriptive analysis.
With SPSS, we were able to run descriptive tests on our data to discover if there was a correlation between the growth of migration/population in Portland neighborhoods and the total area of green spaces. We also wanted to see if there existed any significant enough results to suggest that population growth influences the distribution of land use. So using the census data that described the population of given neighborhoods from 1980 and 2010, we conducted a test for correlation with the population numbers of 1980 with their corresponding access to green spaces, and again with the 2010 census numbers. We then found the percentage change for each neighborhood. Using this number, we again conducted correlation tests with their corresponding access to green spaces. These tests proved significant in their findings.