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Progress in Spatial Demography()

BACKGROUND: Demography is an inherently spatial science, yet the application of spatial data and methods to demographic research has tended to lag that of other disciplines. In recent years, there has been a surge in interest in adding a spatial perspective to demography. This sharp rise in interest...

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Autores principales: Matthews, Stephen A., Parker, Daniel M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7454172/
https://www.ncbi.nlm.nih.gov/pubmed/32863759
http://dx.doi.org/10.4054/demres.2013.28.10
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author Matthews, Stephen A.
Parker, Daniel M.
author_facet Matthews, Stephen A.
Parker, Daniel M.
author_sort Matthews, Stephen A.
collection PubMed
description BACKGROUND: Demography is an inherently spatial science, yet the application of spatial data and methods to demographic research has tended to lag that of other disciplines. In recent years, there has been a surge in interest in adding a spatial perspective to demography. This sharp rise in interest has been driven in part by rapid advances in geospatial data, new technologies, and methods of analysis. OBJECTIVES: We offer a brief introduction to four of the advanced spatial analytic methods: spatial econometrics, geographically weighted regression, multilevel modeling, and spatial pattern analysis. We look at both the methods used and the insights that can be gained by applying a spatial perspective to demographic processes and outcomes. To help illustrate these substantive insights, we introduce six papers that are included in a Special Collection on Spatial Demography. We close with some predictions for the future, as we anticipate that spatial thinking and the use of geospatial data, technology, and analytical methods will change how many demographers address important demographic research questions. CONCLUSION: Many important demographic questions can be studied and framed using spatial approaches. This will become even more evident as changes in the volume, source, and form of available demographic data—much of it geocoded—further alter the data landscape, and ultimately the conceptual models and analytical methods used by demographers. This overview provides a brief introduction to a rapidly changing field.
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spelling pubmed-74541722020-08-28 Progress in Spatial Demography() Matthews, Stephen A. Parker, Daniel M. Demogr Res Article BACKGROUND: Demography is an inherently spatial science, yet the application of spatial data and methods to demographic research has tended to lag that of other disciplines. In recent years, there has been a surge in interest in adding a spatial perspective to demography. This sharp rise in interest has been driven in part by rapid advances in geospatial data, new technologies, and methods of analysis. OBJECTIVES: We offer a brief introduction to four of the advanced spatial analytic methods: spatial econometrics, geographically weighted regression, multilevel modeling, and spatial pattern analysis. We look at both the methods used and the insights that can be gained by applying a spatial perspective to demographic processes and outcomes. To help illustrate these substantive insights, we introduce six papers that are included in a Special Collection on Spatial Demography. We close with some predictions for the future, as we anticipate that spatial thinking and the use of geospatial data, technology, and analytical methods will change how many demographers address important demographic research questions. CONCLUSION: Many important demographic questions can be studied and framed using spatial approaches. This will become even more evident as changes in the volume, source, and form of available demographic data—much of it geocoded—further alter the data landscape, and ultimately the conceptual models and analytical methods used by demographers. This overview provides a brief introduction to a rapidly changing field. 2013-02-13 2013 /pmc/articles/PMC7454172/ /pubmed/32863759 http://dx.doi.org/10.4054/demres.2013.28.10 Text en This open-access work is published under the terms of the Creative Commons Attribution NonCommercial License 2.0 Germany, which permits use, reproduction & distribution in any medium for non-commercial purposes, provided the original author(s) and source are given credit. See http://creativecommons.org/licenses/by-nc/2.0/de/
spellingShingle Article
Matthews, Stephen A.
Parker, Daniel M.
Progress in Spatial Demography()
title Progress in Spatial Demography()
title_full Progress in Spatial Demography()
title_fullStr Progress in Spatial Demography()
title_full_unstemmed Progress in Spatial Demography()
title_short Progress in Spatial Demography()
title_sort progress in spatial demography()
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7454172/
https://www.ncbi.nlm.nih.gov/pubmed/32863759
http://dx.doi.org/10.4054/demres.2013.28.10
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