In a new paper in the International Journal of Digital Humanities, CURA Director Harvey Miller and Assosciate Director Ningchuan Xiao, along with CURA staff, use machine learning and GIS to create 3D urban models from historical Sanborn fire insurance maps.

 

 

In the Ghost Neighborhoods of Columbus project, we are developing and apply- ing 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 story- telling 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.

 

Harvey J.Miller, Ningchuan Xiao, Matthew Lewis, Mostahidul Alam, Oliver Gwynn, Tshui Mum Ha, Michelle Hooper, Karyn Kerdolff, Gavin Levine, Yuantai Li, Mahnoush Mostafavisabet, Joshua Sadvari, Josie Stiver, Jordan Swaim-Fox, ShubhThakkar, Ahmad IlderimTokey, Shelbi Toone, Di Wang