A new tool for neighbourhood change research: The Canadian Longitudinal Census Tract Database, 1971–2016.

Performing longitudinal analysis of socio‐economic change in small‐area spatial units such as census tracts presents several methodological complications and requires significant data preparation. Unit boundaries are revised each census year because of changes in population and delineation methodolo...

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Publicado en:Canadian Geographer Vol. 62; no. 4; pp. 575 - 589
Autores principales: Allen, Jeff, Taylor, Zack
Formato: Artículo
Publicado: Wiley-Blackwell Winter2018
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        10.1111/cag.12467
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        atl: A new tool for neighbourhood change research: The Canadian Longitudinal Census Tract Database, 1971–2016.
      aug:
        au:
          Allen, Jeff
          Taylor, Zack
        affil:
          Department of Geography & Planning, University of Toronto
          Department of Political Science, University of Western Ontario
      su:
        Census
        Neighborhood change
        Geographic information systems
        Databases
        Preparation of data in electronic data processing
      sug:
        subj:
          Census
          Neighborhood change
          Data Processing, Hosting, and Related Services
          Geographic information systems
          Databases
          Preparation of data in electronic data processing
      keyword:
        areal interpolation
        census tracts
        GIS
        historical geography
        neighbourhood change
        changement dans le voisinage
        géographie historique
        interpolation spatiale
        secteurs de recensement
        SIG
        areal interpolation
        census tracts
        GIS
        historical geography
        neighbourhood change
        changement dans le voisinage
        géographie historique
        interpolation spatiale
        secteurs de recensement
        SIG
      ab: Performing longitudinal analysis of socio‐economic change in small‐area spatial units such as census tracts presents several methodological complications and requires significant data preparation. Unit boundaries are revised each census year because of changes in population and delineation methodologies. This limits cross‐year comparison since data are not representative of the same spatial units. To address these problems, we have developed an innovative procedure to reduce error when comparing tract‐level data across census years by apportioning data to the same areal units. This paper describes the methods used to create the Canadian Longitudinal Tract Database. Our procedure is a combination of map‐matching techniques, dasymetric overlays, and population‐weighted areal interpolation. The output is a set of tables with apportionment weights pertaining to pairs of unique boundary identifiers across census years, which can be linked with census data or other data with census identifiers that require longitudinal comparison. Key Messages: Neighbourhood change research is challenged by census boundaries being revised each census year.This paper describes the creation of a longitudinal spatial database of census tracts in Canada, bridging tract‐level data for the 1971–2016 quinquennial censuses to a common set of boundaries.Methodology includes map‐matching, dasymetric overlays, and population‐weighted areal interpolation in order to minimize error when boundaries change over time.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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