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Spatial Data Analysis

Models, Methods and Techniques

  • Book
  • © 2011

Overview

Authors:
  1. Manfred M. Fischer

    1. Business, Socio Economics, Vienna University of Economic and, Vienna, Austria

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  2. Jinfeng Wang

    1. IGSNRR, State Key Laboratory of Resources &, Chinese Academy of Sciences, Beijing, China, People's Republic

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    You can also search for this author in PubMed   Google Scholar

  • The book helps the reader
  • Provides a quick overview of the best practice models, methods and techniques in spatial data analysis
  • Shows how to correctly interpret the results of spatial regression models, an issue that had been largely neglected in the past
  • Demonstrates how to relax the independence assumption in spatial interaction modelling to account for the spatial dependence in origin-destination flows

Part of the book series: SpringerBriefs in Regional Science (BRIEFSREGION)

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Table of contents (5 chapters)

  1. Front Matter

    Pages i-viii
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  2. Introduction

    • Manfred M. Fischer, Jinfeng Wang
    Pages 1-11

  3. The Analysis of Area Data

    1. Front Matter

      Pages 13-13
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  4. The analysis of area data

    1. Exploring Area Data

      • Manfred M. Fischer, Jinfeng Wang
      Pages 15-29

    2. Modelling Area Data

      • Manfred M. Fischer, Jinfeng Wang
      Pages 31-44

  5. The Analysis of Spatial Interaction Data

    1. Front Matter

      Pages 45-46
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  6. The analysis of spatial interaction data

    1. Models and Methods for Spatial Interaction Data

      • Manfred M. Fischer, Jinfeng Wang
      Pages 47-59

    2. Spatial Interaction Models and Spatial Dependence

      • Manfred M. Fischer, Jinfeng Wang
      Pages 61-70

  7. Back Matter

    Pages 71-82
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Keywords

About this book

The availability of spatial databases and widespread use of geographic information systems has stimulated increasing interest in the analysis and modelling of spatial data. Spatial data analysis focuses on detecting patterns, and on exploring and modelling relationships between them in order to understand the processes responsible for their emergence. In this way, the role of space is emphasised , and our understanding of the working and representation of space, spatial patterns, and processes is enhanced. In applied research, the recognition of the spatial dimension often yields different and more meaningful results and helps to avoid erroneous conclusions. This book aims to provide an introduction into spatial data analysis to graduates interested in applied statistical research. The text has been structured from a data-driven rather than a theory-based perspective, and focuses on those models, methods and techniques which are both accessible and of practical use for graduate students. Exploratory techniques as well as more formal model-based approaches are presented, and both area data and origin-destination flow data are considered.

Reviews

From the reviews:

“Fischer and Wang detail the models, methods, and techniques that can be employed to describe and explain the pattern and behaviour of variables distributed over geographic space. … This is a wholly useful text, aimed at quantitative geographers and spatial econometricians who … want to develop their skills further. It would be ideal for masters-level students in GIS, spatial analysis, and econometrics as well as for the increasing body of researchers who are beginning to see the value of accounting for space in their models.” (Daniel Lewis, Environmental and Planning B: Planning and Design, Vol. 39 (4), 2012)

Authors and Affiliations

  • Business, Socio Economics, Vienna University of Economic and, Vienna, Austria

    Manfred M. Fischer

  • IGSNRR, State Key Laboratory of Resources &, Chinese Academy of Sciences, Beijing, China, People's Republic

    Jinfeng Wang

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