From historical maps to lived experiences: A community-engaged approach to 3D urban modeling of neighborhoods prior to urban highways and urban renewal

In the Ghost Neighborhoods of Columbus project, we are developing and applying machine learning (ML) and geographic information science (GIS) methods to extract data from historical Sanborn fire insurance maps and build 3D urban models of how neighborhoods looked in the past. We are focusing on historically Black neighborhoods in Columbus that have been altered by urban highway construction, urban renewal and redlining practices. We are working with neighborhood members and community partners to identify neighborhoods for investigation, model use cases, design features and delivery modes. We are also collecting stories, memories and photos with the intent of using the 3D urban models as platforms for storytelling about lived experiences in these lost places. In this paper, we describe our approaches to 3D model development, model delivery and community engagement. We identify and discuss issues and bottlenecks we discovered, and strategies for resolving these problems.