Urban Analytics and Spatial Data Management (MiniClass)

This mini-class provides a hands-on, "quick start" look at some of the methods and tools that help urban planners capitalize on the new world of ubiquitous urban sensing and pervasive computing. Translating the new data streams into useful urban analytics and a deeper understanding of activity patterns and sustainability issues is exciting but challenging. The mini-class cannot cram a whole course into a few sessions, but they can provide hands-on experience with 'real world' datasets that can introduce enough of the methods and tools to wet one's appetite and facilitate subsequent self-teaching. We assume students are familiar with at least 11.205 (GIS) and 11.220 (basic statistics) and basic data management using a tool such as MS-Access or MS-Excel (There will not be time in the mini-class to fill in those basics.)  We will use R, ArcGIS, QGIS, PostgreSQL, PostGIS, and MS-Access for model estimation, data management, indicator development, spatial analysis, and visualization.  Optional lab sessions (on Fridays) will provide extra help with R, QGIS, and Postgres for those who are eager and able but have limited experience with these tools.

 The mini-class is organized as a workshop with two introductory lectures followed by hands-on lab sessions that involve structured lab exercises plus open-ended project work using datasets and tools discussed in the lectures.  Prior to the first session, participants will read portions of a PhD dissertation authored by a recent Urban Information Systems (UIS) graduate.  The first two sessions will be a lecture and demonstration of the data, methods, and results of specific empirical analyses in the dissertation.  Subsequent sessions will be hands-on lab exercises using the data and exploring alternative models, hypotheses, indicators, and visualizations.  During the fourth week, participants will present their analyses and interpretations of the data, and the final week will introduce further analysis and exploration methods.  The PhD dissertation that will provide the data and point of departure for the mini-classes is by Dr. Mi Diao who received his PhD from DUSP in 2010 and is now an Assistant Professor in the Real Estate Department within the School of Design and Environment at the National University of Singapore.  His dissertation, “Sustainable Metropolitan Growth Strategies: Exploring the Role of the Built Environment" is available on MIT’s DSpace: https://dspace.mit.edu/handle/1721.1/62125Prof. Diao's dissertation examines the interactions among indicators of built environment, demographics, land use, housing prices, and vehicle miles travelled  using spatially detailed data (including annual mileage estimates for several million Massachusetts private passenger vehicles geocoded by place of garaging).  Participants in the mini-classes will be given access to the data and tools used in this dissertation for the mini-class exercises and an individual or small group miniproject.