Chapter 1 Geospatial Analysis and Modeling of Urban Structure and Dynamics: An Overview

Geographic information research and technologies have experienced over four decades of development, from the mainframe to the workstation to the desktop, and to today's laptop and mobile devices. Every important GIS development is driven by a significant breakthrough of mainstream information technology. For example, the 1980s was characterized by the popularity of personal computers that were in-creasingly becoming affordable to university departments, governmental agencies and private sectors. Many university GIS programs were established during this time period, and the NSF-funded NCGIA played an important role in coordinating the development of course curriculum and related research activities. The next decade can be named the age of GIScience. GIScience is the science behind GI-Systens, dealing with fundamental questions raised by the use of GISystems and technologies (Goodchild 1997). It occurred at the time when the Internet and the World Wide Web started to change the way we led our lives and ran our businesses. It was the Internet and the Web that made the GIS community think of a service oriented approach to GIS, namely GIServices (Gunther and Muller 1999). Instead of owning a GIS, end users can be served by GIS functionalities from a remote GIService center. GIServices aim to develop distributed or decentralized GIS to serve individuals and communities for spatial planning and decision making, as well as for their daily life. Another perspec tive of GIS is GIStudies for studying the impacts of geographic information and technologies on society. The above GIS related terms reflect from one dimension how GIS has evolved from a computer-based centralized system, to an internet-or-web-based decentral-ized service; from the technologically dominated view to the increasingly science oriented view, and to a broader societal perspective. Along the technological di-mension, GIS has evolved from initial 2D maps to 3D representations, from static maps to animated visualization, from stationary computers to mobile devices, and from being professionally oriented to catering to the general public. The continuous

[1]  B. Hillier,et al.  The Social Logic of Space , 1984 .

[2]  S. Albeverio.  The dynamics of complex urban systems : an interdisciplinary approach , 2008 .

[3]  D. Pumain.  Hierarchy in natural and social sciences , 2006 .

[4]  Bin Jiang,et al.  Self-organized natural roads for predicting traffic flow: a sensitivity study , 2008, 0804.1630.

[5]  Nikos A. Salingaros,et al.  Principles of Urban Structure , 2008 .

[6]  Declan Butler,et al.  Virtual globes: The web-wide world , 2006, Nature.

[7]  Daniel Z. Sui,et al.  The wikification of GIS and its consequences: Or Angelina Jolie's new tattoo and the future of GIS , 2008, Comput. Environ. Urban Syst..

[8]  P. Torrens,et al.  Geosimulation: Automata-based modeling of urban phenomena , 2004 .

[9]  E. Ma.  Handbook of Research on Urban Informatics: The Practice and Promise of the Real-Time City , 2009 .

[10]  Michael Batty,et al.  Advanced Spatial Analysis: The CASA Book of GIS , 2003 .

[11]  Sergio Albeverio,et al.  The Dynamics of Complex Urban Systems , 2008 .

[12]  Ron Atkin,et al.  Mathematical structure in human affairs , 1976 .

[13]  Bin Jiang,et al.  Street hierarchies: a minority of streets account for a majority of traffic flow , 2008, Int. J. Geogr. Inf. Sci..

[14]  Kevin Lynch,et al.  The Image of the City , 1960 .

[15]  Vassilis Kostakos,et al.  Cityware: Urban Computing to Bridge Online and Real-World Social Networks , 2008 .

[16]  Oliver Günther,et al.  From GISystems to GIServices: Spatial Computing on the Internet Marketplace , 1999 .

[17]  Michael Batty,et al.  Cities and Complexity: Understanding Cities Through Cellular Automata, Agent-Based Models and Fractals , 2005 .

[18]  Michael Batty,et al.  Cities and complexity - understanding cities with cellular automata, agent-based models, and fractals , 2007 .

[19]  Dino Pedreschi,et al.  Mobility, Data Mining and Privacy - Geographic Knowledge Discovery , 2008, Mobility, Data Mining and Privacy.

[20]  M. Goodchild.  Citizens as sensors: the world of volunteered geography , 2007 .

[21]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[22]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[23]  B. Jiang.  A topological pattern of urban street networks: Universality and peculiarity , 2007, physics/0703223.