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Designing and implementing software for spatial statistical analysis in a GIS environment

Author

Listed:
  • Robert Haining

    (Department of Geography, Sheffield Centre for Geographic Information and Spatial Analysis, University of Sheffield, UK (e-mail: R.Haining@Sheffield.ac.uk))

  • Stephen Wise

    (Department of Geography, Sheffield Centre for Geographic Information and Spatial Analysis, University of Sheffield, UK (e-mail: R.Haining@Sheffield.ac.uk))

  • Jingsheng Ma

    (Department of Geography, Sheffield Centre for Geographic Information and Spatial Analysis, University of Sheffield, UK (e-mail: R.Haining@Sheffield.ac.uk))

Abstract

. This paper provides a description of SAGE, a software package linked to the Arc/Info GIS that can be used to undertake spatial statistical analysis of area based data. The paper is written from the perspective of the user who wishes to undertake exploratory and confirmatory spatial data analysis. The paper discusses design aspects of the package and also the statistical analysis philosophy underlying its contents. The paper describes the statistical analyses which SAGE can perform and details on how it performs them together with some illustrative examples. Detail on visualisation aspects of SAGE are discussed in a separate paper (Haining et al. 2000). The wider contribution of the paper is to build on earlier developments in this area and identify the needs of software packages if they are to enable users to implement effective spatial statistical analysis.

Suggested Citation

  • Robert Haining & Stephen Wise & Jingsheng Ma, 2000. "Designing and implementing software for spatial statistical analysis in a GIS environment," Journal of Geographical Systems, Springer, vol. 2(3), pages 257-286, September.
    • Handle: RePEc:kap:jgeosy:v:2:y:2000:i:3:d:10.1007_pl00011458
    DOI: 10.1007/PL00011458
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    Citations

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    Cited by:

    1. Elizabeth Mack & Yifan Zhang & Sergio Rey & Ross Maciejewski, 2014. "Spatio-temporal analysis of industrial composition with IVIID: an interactive visual analytics interface for industrial diversity," Journal of Geographical Systems, Springer, vol. 16(2), pages 183-209, April.
    2. Ángeles Sánchez & Jorge Chica-Olmo & Juan de Dios Jiménez-Aguilera, 2018. "A Space–Time Study for Mapping Quality of Life in Andalusia During the Crisis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(2), pages 699-728, January.
    3. Pablo Quintana, 2022. "Una metodología de clustering para agrupar series temporales en regiones contiguas," Asociación Argentina de Economía Política: Working Papers 4589, Asociación Argentina de Economía Política.
    4. Pablo Aníbal Quintana, 2021. "Métodos de clustering espacialmente restringidos: Un análisis al agrupamiento por nivel de estudio en la provincia de Mendoza," Asociación Argentina de Economía Política: Working Papers 4510, Asociación Argentina de Economía Política.
    5. Massimo Craglia & Robert Haining & Paola Signoretta, 2001. "Modelling High-intensity Crime Areas in English Cities," Urban Studies, Urban Studies Journal Limited, vol. 38(11), pages 1921-1941, October.
    6. Kifayat Ullah & M. Tariq Majeed & Ghulam Mustafa, 2020. "Exploring Spatial Patterns and Determinants of Poverty: New Evidence from Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 59(3), pages 439-459.

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