A Proposed Method for Spatial Data Disaggregation and Interpolation.

The Model for External Reliance of Localities in (MERLIN) Coastal Management Zones is a proposed solution to allow scaling of variables to smaller, nested geographies. Using a principal components analysis and data normalization techniques, smaller scale data relationships are linked to data relatio...

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Publicado en:Professional Geographer Vol. 69; no. 1; pp. 70 - 80
Autor principal: Buck, Kyle D.
Formato: Artículo
Publicado: Taylor & Francis Ltd Feb2017
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2017
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      pub: Taylor & Francis Ltd
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        10.1080/00330124.2016.1158116
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        atl: A Proposed Method for Spatial Data Disaggregation and Interpolation.
      aug:
        au: Buck, Kyle D.
        affil: USEPA/ORD/NHEERL, Gulf Ecology Division
      su:
        Scaling (Social sciences)
        Interpolation
        Coastal zone management
        Spatial data structures
        Geographic information systems
      sug:
        subj:
          Scaling (Social sciences)
          Interpolation
          Coastal zone management
          Spatial data structures
          Geographic information systems
      keyword:
        data interpolation
        Florida
        nested geographies
        principal components analysis
        scaling
        análisis de componentes principales
        análisis de componentes principales
        escalar
        geografías anidadas
        geografías anidadas
        interpolación de datos
        interpolación de datos
        data interpolation
        Florida
        nested geographies
        principal components analysis
        scaling
        análisis de componentes principales
        análisis de componentes principales
        escalar
        geografías anidadas
        geografías anidadas
        interpolación de datos
        interpolación de datos
      ab: The Model for External Reliance of Localities in (MERLIN) Coastal Management Zones is a proposed solution to allow scaling of variables to smaller, nested geographies. Using a principal components analysis and data normalization techniques, smaller scale data relationships are linked to data relationships within larger geographies and scaling factors are developed for each. In using these relationships, MERLIN will derive a set of variables scaled to a desired geography representing the attributes of the population present. The concept driving MERLIN's development is that correlations between variables at a specific location and level of geography can be tested and applied to other scales for interpolations. This flexibility and relative simplicity of calculation make MERLIN a valuable tool in many types of social research and for data interpolation. In a pilot study, the MERLIN model is applied to counties along the Gulf Coast of Florida to create a well-being index at the census tract level. Results reveal a landscape that better accounts for the localized patterns of values situated within a larger geographic unit.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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