Sean Capperis

Adjunct Assistant Professor of Urban Planning

Sean Capperis is an Adjunct Assistant Professor of Urban Planning at the NYU Wagner Graduate School of Public Service. He also serves as Director of Strategic Planning at the New York City Department of Housing Preservation and Development, where he manages the development of new policy initiatives.

Previously, Capperis served as Data Manager and Research Analyst at the NYU Furman Center for Real Estate and Urban Policy, where he oversaw quantiative analysis activities, data management, and technical training. Prior to joining NYU, Capperis was an analyst with the New York City Department of Finance and held various research and communications roles for local government and civic organizations in Pittsburgh.

Capperis holds a B.A. in Urban Studies and English Writing from the University of Pittsburgh and an M.P.A. from NYU Wagner, where he was a David Bohnett Public Service Fellow.

Sophisticated analysis of spatial data in geographic information systems (GIS) is becoming increasingly necessary to support discovery and decision-making in urban planning and policy. This course will cover several spatial analysis methods as well as the visualization and data management techniques that support these methods. Topics will include network analysis as applied in transportation; areal interpolation and geographic crosswalks as applied in demographics; point density and basic interpolation (heat maps) as applied in public safety and housing; and replication through ModelBuilder. We will place each topic in a policy-oriented, problem-solving analytical framework that students can apply across a variety of contexts. Lab exercises and assignments will focus on current issues in New York City, and students will expand their knowledge of open spatial data sets. The course will culminate in a student-defined, portfolio quality final project.

Download Syllabus

Sophisticated analysis of spatial data in geographic information systems (GIS) is becoming increasingly necessary to support discovery and decision-making in urban planning and policy. This course will cover several spatial analysis methods as well as the visualization and data management techniques that support these methods. Topics will include network analysis as applied in transportation; areal interpolation and geographic crosswalks as applied in demographics; point density and basic interpolation (heat maps) as applied in public safety and housing; and replication through ModelBuilder. We will place each topic in a policy-oriented, problem-solving analytical framework that students can apply across a variety of contexts. Lab exercises and assignments will focus on current issues in New York City, and students will expand their knowledge of open spatial data sets. The course will culminate in a student-defined, portfolio quality final project.

Download Syllabus

Sophisticated analysis of spatial data in geographic information systems (GIS) is becoming increasingly necessary to support discovery and decision-making in urban planning and policy. This course will cover several spatial analysis methods as well as the visualization and data management techniques that support these methods. Topics will include network analysis as applied in transportation; areal interpolation and geographic crosswalks as applied in demographics; point density and basic interpolation (heat maps) as applied in public safety and housing; and replication through ModelBuilder. We will place each topic in a policy-oriented, problem-solving analytical framework that students can apply across a variety of contexts. Lab exercises and assignments will focus on current issues in New York City, and students will expand their knowledge of open spatial data sets. The course will culminate in a student-defined, portfolio quality final project.

Download Syllabus