progress in spatial demography
Clicks: 92
ID: 221697
2013
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
27.3
/100
92 views
28 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #93 of 101 articles by views in journal of urban planning and development
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
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. OBJECTIVE 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. CONCLUSIONS 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 geocode - -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.
| Reference Key |
matthews2013demographicprogress
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Stephen A. Matthews;Daniel M. Parker |
| Journal | journal of urban planning and development |
| Year | 2013 |
| DOI |
DOI not found
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.