Jacquez2000221

Référence

Jacquez, G.M., Maruca, S. and Fortin, M.-J. (2000) From fields to objects: A review of geographic boundary analysis. Journal of Geographical Systems, 2(3):221-241. (Scopus )

Résumé

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.

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@ARTICLE { Jacquez2000221,
    AUTHOR = { Jacquez, G.M. and Maruca, S. and Fortin, M.-J. },
    TITLE = { From fields to objects: A review of geographic boundary analysis },
    JOURNAL = { Journal of Geographical Systems },
    YEAR = { 2000 },
    VOLUME = { 2 },
    NUMBER = { 3 },
    PAGES = { 221-241 },
    NOTE = { cited By 84 },
    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. },
    AFFILIATION = { BioMedware, 516 North State Street, Ann Arbor, MI 48104-1236, United States; Departement de Geographie, Universit de Montreal, C.P. 6128 Succ. Centre-Ville, Montreal, Que. H3C 3J7, Canada },
    AUTHOR_KEYWORDS = { Boundary; Boundary detection; Object definition; Spatial analysis; Spatial software },
    DOCUMENT_TYPE = { Review },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-0033794641&partnerID=40&md5=75b97b3bb35918b3f4b7ab8a31de3fe6 },
}

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