Urban Informatics

Urban Informatics

Author: Wenzhong Shi

Publisher: Springer Nature

Published: 2021-04-06

Total Pages: 941

ISBN-13: 9811589836

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This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.


Modeling Urban Dynamics

Modeling Urban Dynamics

Author: Marius Thériault

Publisher: John Wiley & Sons

Published: 2013-02-04

Total Pages: 350

ISBN-13: 1118601653

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The field of Urban Dynamics itself is based on the systems engineering concept that all complex systems (and cities and urban areas are no exception) are comprised of independent and often smaller, more understandable sub-components with relationships to one another. This allows for the system as a whole to be modeled, using knowledge of the individual subsystems and their behaviors. In this instance, urban dynamics allows for the modeling and understanding of land use, the attractiveness of space to residents, and how the ageing and obsolescence of buildings affects planning and economic development, as well as population movements, with the urban landscape. The book adopts a trans-disciplinary approach that looks at the way residential mobility, commuting patterns, and travel behavior affect the urban form. It addresses a series of issues dealing with the accessibility of urban amenities, quality of life, and assessment of landscape residential choices, as well as measurement of external factors in the urban environment and their impact on property values.


Geospatial Analysis and Modelling of Urban Structure and Dynamics

Geospatial Analysis and Modelling of Urban Structure and Dynamics

Author: Bin Jiang

Publisher: Springer Science & Business Media

Published: 2010-06-16

Total Pages: 465

ISBN-13: 9048185726

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A Coming of Age: Geospatial Analysis and Modelling in the Early Twenty First Century Forty years ago when spatial analysis first emerged as a distinct theme within geography’s quantitative revolution, the focus was largely on consistent methods for measuring spatial correlation. The concept of spatial au- correlation took pride of place, mirroring concerns in time-series analysis about similar kinds of dependence known to distort the standard probability theory used to derive appropriate statistics. Early applications of spatial correlation tended to reflect geographical patterns expressed as points. The perspective taken on such analytical thinking was founded on induction, the search for pattern in data with a view to suggesting appropriate hypotheses which could subsequently be tested. In parallel but using very different techniques came the development of a more deductive style of analysis based on modelling and thence simulation. Here the focus was on translating prior theory into forms for generating testable predictions whose outcomes could be compared with observations about some system or phenomenon of interest. In the intervening years, spatial analysis has broadened to embrace both inductive and deductive approaches, often combining both in different mixes for the variety of problems to which it is now applied.