The economic and political situation of cities has shifted in recent years in light of rapid growth amidst infrastructure decline, the suburbanization of poverty and inner city revitalization. At the same time, the way that data are used to understand urban systems has changed dramatically. Urban Analytics offers a field-defining look at the challenges and opportunities of using new and emerging data to study contemporary and future cities through methods including GIS, Remote Sensing, Big Data and Geodemographics. Written in an accessible style and packed with illustrations and interviews from key urban analysts, this is a groundbreaking new textbook for students of urban planning, urban design, geography, and the information sciences.

Urban Data Infrastructure

Urban Data Infrastructure

Learning Objectives

By the end of this chapter students will understand the following:

  • The purpose and importance of computing infrastructure to urban analytics.
  • The essential components of a computer, and those locations where computation can occur.
  • Some differentiating characteristics of software languages and their appropriate use.
  • How data are stored within a computing environment.
  • The environmental consequences of computing.

Data Infrastructure for Urban Analytics

The storage, analysis and dissemination of data rely on computer hardware and software resources. Just a few years ago, this book would have mainly been relevant to researchers interested in devoting considerable time to developing programming solutions from scratch, and to those who had access to high-end computational resources. However, as hardware prices have fallen, and software tools have become more user friendly, ...

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