Modeling Community Land Trust Property Locations within Vulnerable Communities

This study presents an analysis of the City of Lakes Community Land Trust in Minneapolis, Minnesota that investigates the relationship between locations of properties in their portfolio (n=251) and the demographics of surrounding neighborhoods. The study seeks to develop and test a methodology for assessing the alignment of Community Land Trust property locations to neighborhoods that would best benefit from affordable housing interventions due to vulnerability to gentrification. An auto-logistic binary logistic regression included the analysis of 8 predictor variables namely: median housing value, percent renter, education ratio (low to highly educated), linguistically isolated, median age, vacancy, non-white population, and median household income at the US Census block group level. A result of 72.17 balanced accuracy for a spatially weighted binary logistic model revealed predicted locations of CLT properties were most influenced by presence of non-white population, percentage of renters and median age. The significant variables were used to create an overall index map of vulnerable target neighborhoods also showed that on the whole, the City of Lakes CLT is aligning to serve high and moderately vulnerable neighborhoods about half of the time. The study offers a quantitative method that may be further developed to better understand this emergent affordable housing model.