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From fields to objects: A review of geographic boundary analysis

Author

Listed:
  • G. M. Jacquez

    (BioMedware, 516 North State Street, Ann Arbor, MI 48104-1236, USA (e-mail: jacquez@biomedware.com))

  • S. Maruca

    (BioMedware, 516 North State Street, Ann Arbor, MI 48104-1236, USA (e-mail: jacquez@biomedware.com))

  • M.-J. Fortin

    (Departement de Geographie, Universit de Montreal, C.P. 6128 Succ. Centre-Ville, Montreal, Quebec H3C 3J7, Canada)

Abstract

. Geographic boundary analysis is a relatively new approach unfamiliar to many spatial analysts. It is best viewed as a technique for defining objects – geographic boundaries – on spatial fields, and for evaluating the statistical significance of characteristics of those boundary objects. This is accomplished using null spatial models representative of the spatial processes expected in the absence of boundary-generating phenomena. Close ties to the object-field dialectic eminently suit boundary analysis to GIS data. The majority of existing spatial methods are field-based in that they describe, estimate, or predict how attributes (variables defining the field) vary through geographic space. Such methods are appropriate for field representations but not object representations. As the object-field paradigm gains currency in geographic information science, appropriate techniques for the statistical analysis of objects are required. The methods reviewed in this paper are a promising foundation. Geographic boundary analysis is clearly a valuable addition to the spatial statistical toolbox.¶ This paper presents the philosophy of, and motivations for geographic boundary analysis. It defines commonly used statistics for quantifying boundaries and their characteristics, as well as simulation procedures for evaluating their significance. We review applications of these techniques, with the objective of making this promising approach accessible to the GIS-spatial analysis community. We also describe the implementation of these methods within geographic boundary analysis software: GEM.

Suggested Citation

  • G. M. Jacquez & S. Maruca & M.-J. Fortin, 2000. "From fields to objects: A review of geographic boundary analysis," Journal of Geographical Systems, Springer, vol. 2(3), pages 221-241, September.
    • Handle: RePEc:kap:jgeosy:v:2:y:2000:i:3:d:10.1007_pl00011456
    DOI: 10.1007/PL00011456
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    Citations

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    Cited by:

    1. Levi J Wolf & Elijah Knaap & Sergio Rey, 2021. "Geosilhouettes: Geographical measures of cluster fit," Environment and Planning B, , vol. 48(3), pages 521-539, March.
    2. Joscha Legewie, 2018. "Living on the Edge: Neighborhood Boundaries and the Spatial Dynamics of Violent Crime," Demography, Springer;Population Association of America (PAA), vol. 55(5), pages 1957-1977, October.
    3. Sam Hui & Eric Bradlow, 2012. "Bayesian multi-resolution spatial analysis with applications to marketing," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 419-452, December.
    4. Haijun Ma & Bradley P. Carlin & Sudipto Banerjee, 2010. "Hierarchical and Joint Site-Edge Methods for Medicare Hospice Service Region Boundary Analysis," Biometrics, The International Biometric Society, vol. 66(2), pages 355-364, June.
    5. Lintz, Heather E. & McCune, Bruce & Gray, Andrew N. & McCulloh, Katherine A., 2011. "Quantifying ecological thresholds from response surfaces," Ecological Modelling, Elsevier, vol. 222(3), pages 427-436.
    6. Thangatur Sukumar Hariharan & L. S. Ganesh & Vijayalakshmi Venkatraman & Piyush Sharma & Vidyasagar Potdar, 2022. "Morphological Analysis of general system–environment complexes: Representation and application," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(2), pages 218-240, March.
    7. Joshua L. Warren & Jiachen Cai & Nicholaus P. Johnson & Nicole C. Deziel, 2022. "A discrete kernel stick‐breaking model for detecting spatial boundaries in hydraulic fracturing wastewater disposal well placement across Ohio," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(1), pages 175-193, January.
    8. Duncan Lee & Richard Mitchell, 2013. "Locally adaptive spatial smoothing using conditional auto-regressive models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(4), pages 593-608, August.
    9. Ilaria Zambon & Pere Serra & Silvia Pili & Vincenzo Bernardini & Carlotta Ferrara & Luca Salvati, 2018. "A New Approach to Land-Use Structure: Patch Perimeter Metrics as a Spatial Analysis Tool," Sustainability, MDPI, vol. 10(7), pages 1-17, June.
    10. Hannah M. Director & Adrian E. Raftery, 2022. "Contour models for physical boundaries enclosing star‐shaped and approximately star‐shaped polygons," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1688-1720, November.

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