Spatial Analysis And Location Modeling In Urban And Regional Systems
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Spatial Analysis and Location Modeling in Urban and Regional Systems
This contributed volume collects cutting-edge research in Geographic Information Science & Technologies, Location Modeling, and Spatial Analysis of Urban and Regional Systems. The contributions emphasize methodological innovations or substantive breakthroughs on many facets of the socio-economic and environmental reality of urban and regional contexts.
Innovations in Urban and Regional Systems
This book presents cutting‐edge research on urban and regional systems applying modern spatial analytical techniques of Geographic Information Science & Technologies (GIS&T), spatial statistics, and location modeling. The contributions, written by leading scholars from around the globe, adopt a spatially explicit analytical perspective and highlight methodological innovations and substantive breakthroughs on many facets of the socioeconomic and environmental reality of urban and regional contexts. The book is divided into three parts: The first part offers an introduction to the research field, while the second part discusses critical issues in urban growth and urban management, presenting case studies on city and urban environments, their growth, data infrastructures and spatial and management issues. The third part then broadens the analysis to the regional scale, addressing growth, convergence and adaptation to new economic and information‐based realities. This book appeals to scholars of spatial and regional sciences as well as to policy decision-makers interested in advanced methods of spatial analysis, location modeling, and GIS&T.
Geospatial Analysis and Modelling of Urban Structure and Dynamics
Author: Bin Jiang
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-06-16
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.