Every traveler is a pedestrian at some point in their trip, but pedestrian networks remain a critically overlooked mode in the research. The most vulnerable road users, pedestrians continue to be at high risk for crashes at night. With the use of spatial estimation, this research examines the interactions between streetlights and pedestrian crashes. Despite the safety advantages of sidewalks, the exact bounds and condition of many pedestrian facilities in the United States are unknown due to the expense of data collection. A method for pedestrian network approximation is introduced in this research which uses curb ramp data to generate scalable pedestrian routes across large metropolitan regions, ready to be employed in connectivity and accessibility analyses. These accessible connectivity results were then correlated with census data from a variety of vulnerable populations to determine the degree of disparity present in pedestrian networks. This dissertation both adapts and introduces employable methodologies for data estimation and approximation to analyze pedestrian safety, accessibility, and equity using geospatial tools and statistical analyses. The results and conclusions of this research inform the best practices for pedestrian lighting, establish a framework for pedestrian network approximation, and quantify the accessible and socioeconomic disparities present in pedestrian networks.