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"An explosive new interdisciplinary field of urban research. This textbook delves into the challenges and opportunities of using new and emerging forms of data to study cities. Topics explored include: data and urban computing infrastructure; sensors and human dynamics; urban modeling; agent-based modeling; [and] visualization and GIS. Over recent years, the way that data are used to understand urban systems has changed dramatically. Cities are constantly adapting to incorporate new technology, and this has fast become a key tool to analysing how cities work. Spanning current and future cities, interviews with key urban analysts, reflective questions and technical case studies, 'Urban analytics' equips the reader with a greater understanding of theory and the technical skills needed for practice." -- rear cover

Abstract
The National Science Foundation-Census Bureau Research Network (NCRN) was established in 2011 to create interdisciplinary research nodes on methodological questions of interest and significance to the broader research community and to the Federal Statistical System (FSS), particularly to the Census Bureau. The activities to date have covered both fundamental and applied statistical research and have focused at least in part on the training of current and future generations of researchers in skills of relevance to surveys and alternative measurement of economic units, households, and persons. This article focuses on some of the key research findings of the eight nodes, organized into six topics: (1) improving census and survey data-quality and data collection methods; (2) using alternative sources of data; (3) protecting privacy and confidentiality by improving disclosure avoidance; (4) using spatial and spatio-temporal statistical modeling to improve estimates; (5) assessing data cost and data-quality tradeoffs; and (6) combining information from multiple sources. The article concludes with an evaluation of the ability of the FSS to apply the NCRN's research outcomes, suggests some next steps, and discusses the implications of this research-network model for future federal government research initiatives.