The Anti-Eviction Mapping Project, a collection of volunteers with a reputation for conducting deep analysis of eviction, gentrification, and housing rights in San Francisco has found a correlation between foreclosure rates, race, and the redlining policies of the 1930’s through a spatial analysis and visualization.
Academic institutions and research centers play an important role in monitoring, evaluating and predicting housing markets. Housing markets influence the demographic makeup and overall health of a neighborhood.
Socioeconomic discrepancies among neighborhoods of different racial and ethnic compositions can often be explained through an analysis of historical policies like redlining, a discriminatory policy that labeled certain neighborhoods with predominantly black neighborhoods as unworthy of financial loans and capital investment that correlated to increases in minority residents.
Telling this story and visualizing the impact of this discriminatory practice has been difficult for cities. The Anti-Eviction Mapping Project is changing that with their approach to location intelligence, delivering insight through visualizing and analyzing location data.
In this mapping project, AEMP enriched eviction data and foreclosure rates with extensive demographic and census information provided by datasets from CARTO’s Data Observatory, adding historical context to their findings. This type of visualization makes it easy to fully understand the realities of urban policy by providing important additional context and insight to the research and advocacy taking place in these spaces.
“Ultimately, redlining has driven both racial stratification and foreclosures, two of the major features of modern gentrification. Contemporary reinvestment in poor areas has not resulted in a lessening of these ails; rather, reinvestment has further increased the strain upon poorer residents and minorities, often leaving them without a place to live.”
Erin McElroy, Director of Anti-Eviction Mapping Project
Cities are complex.
Today’s cities are a product of the people that inhabit them, past and present policies, and fluctuating economic markets that help determine the rate of growth or decline. The multitude of trends any given city might experience over time are better understood and communicated by taking a location intelligence approach to visualizing and analyzing your city’s location data.
How have historic policies affected your city’s foreclosure rates or influenced the demographic makeup of neighborhoods and communities? We would love you to show us! CARTO’s Github Developer’s Package and the Grants For Good Program allow professors, students, non-profit organizations and companies, to access Location Intelligence tools? for free.
Happy Data Mapping!
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