11.523 | Fall (H1) 2023

Fundamentals of Spatial Database Management

Department of Urban Studies and Planning , Massachusetts Institute of Technology


Tu Th 10:30-12:30 (Lecture)
Undergrad | Graduate
2-2-2 Units


Spatial Analysis, Data Modeling, Ontological Thinking, SQL


QGIS, PostGIS, PostgreSQL

Advances in urban science, the rise of ‘big data’, the drive to build smarter cities, and the widespread embrace of the open data movement are coalescing into new opportunities for planners to develop varied representations of urban environments requiring large quantities of data. Even as these contemporary discourses and innovations proceed apace, urban archives are richer and more available than ever before. This poses challenges to planning, as a community of practice: to be more contextual, even as naive empiricism becomes ever-more-tempting; to be more historical, even as the present demands ever more of our attention. Technically, it also implies that planners will benefit from a familiarity with formal spatial databases and query languages, including SQL.

Data produced and distributed in a vacuum is worthless, and worse: it might lead us to think that evidence can be divorced from its place and context. As such, we will strive to produce contextually-rich and historically-situated datasets. Using materials from the Leventhal Map & Education Center at the Boston Public Library, we will be creating historical GIS models of Boston-area maps—materials produced by the Boston Redevelopment Authority during and after the height of urban renewal, zoning maps, and fire insurance atlases.