Existing scholarly work demonstrates that the built environment can affect the frequency of motor vehicle (MV) crashes. The objective of this study is to explore the relationship between urban MV traffic crashes at road intersections and the built environment in the city of Des Moines. The study area includes low-income and wealthy neighborhoods to understand the built environment in these different contexts. Exploratory Spatial Data Analysis (ESDA) is used to identify MV crash hotspots at intersections. Google Street View (GSV) is used as a tool to survey the built environment variables such as commercial/institutional land uses, schools, parks, signage, number of lanes, on-street parking, bus stops, etc. of the hotspot intersections. Multiple linear regression and a Tobit model is then employed to establish a relationship between MV traffic crash hotspots at intersections and the built environment. The study considers the statistical significance of the MV crash locations; hence it employs an exploratory spatial data analysis in analyzing MV traffic crashes. This exploratory case study was conducted using 7-year data of vehicle crashes from 2013 to 2019 obtained from the Iowa Department of Transportation (IDOT). The study results indicate that commercial/institutional land uses, bus stops, and signalized intersections are significant built environment variables that impact the occurrence of MV traffic crashes. Additionally, the results also show that MV traffic crash hotspot intersections were in areas with a high household poverty percentage. These results can inform policymakers to develop strategies that focus on suitable MV traffic safety, such as traffic calming measures in hotspot locations. Design ideas to improve the built environment and a policy framework for bus stop locations can be developed, thus preventing and reducing MV traffic crashes