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This study uses building footprints from Microsoft and OpenStreetMap and the Python package momepy to measure the shape, size, and placement of buildings and their 5, 10, and 20 nearest neighbors across the continental United States. Using building and neighborhood morphology and machine learning estimates, we predict whether each building is a singlewide manufactured home and whether it is in a manufactured home park, informal or manufactured home subdivision, or another setting. We describe the methods used to create these predictions and discuss issues of model performance and their implications for future research, compare our estimates with the locations of manufactured homes documented in the American Community Survey and with government and private registries of these communities, illustrate their distribution nationwide, and present descriptive statistics on their demographic and socioeconomic characteristics. Our findings illustrate that manufactured home parks are more common in Midwestern and Northeastern states, whereas informal or manufactured home subdivisions are more common in Southern and Western states. We find that both neighborhoods are demographically diverse but economically disadvantaged. We conclude by briefly discussing the implications of our research for state and federal housing policy. 

Manufactured housing is the largest source of unsubsidised affordable housing in the United States, but the extent of this affordability varies considerably depending upon whether residents own or lease the land on which the unit sits. To date, there have been relatively few analyses of variation across the different contexts in which manufactured homes are located, including in manufactured home parks and on individual plots in residential subdivisions. This is due in part to the limited data on the location of these different community types. In this study, we leverage data from a variety of sources to examine the various contexts in which manufactured housing is sited and differences in the characteristics of dwelling units and their tenure and legal status across these contexts. To do so, we combine parcel-level records documenting land use classifications across 19 counties in Texas, 5.4 million building footprints from Microsoft and OpenStreetMap, manufactured home sales records from the Texas Department of Housing and Community Affairs and registries of parks and subdivisions from the Department of Homeland Security and the Texas Office of the Attorney General, respectively. Using this dataset, we examine variation in the various types of neighbourhoods in which manufactured housing is common and examine the coverage of the state and federal registries of these communities, illustrating that a substantial number of parks and subdivisions are not currently documented in these registries and thus are likely not receiving sufficient government support, including for infrastructure and housing investment or emergency management response.