Tag Archives: spatial demography

Data and code for my columns

I would like to share the original data and code I use in all of the, well, software and code column.  I’m using Figshare to host all of this, and will try to keep it organized by column. Here is the data and original code for the first column, with the column found here and the  second column found here.  Thanks!


Future Directions in Spatial Demography (Final Report, released May 2012)

The Final Report from the Future Directions in Spatial Demography may be of interest to the readers of the new journal, Spatial Demography.

The Future Directions meeting was held in December 2011 in Santa Barbara and included participation from 40+ scholars from demography-related disciplines including geography, economics, sociology, anthropology, political science, and rural sociology. The Final Report was released in April 2012 and made available at the following website:


Matthews, S.A., Janelle, D.G., and Goodchild, M.F. (2012). Future directions in spatial demography: Final report. (Final Report of a Specialist Meeting held December 12-13, 2011, Santa Barbara, CA).

The Future Directions website also includes links to participant presentations and short position statements submitted by each of the meeting attendees.


– Stephen


Public Use Microdata Area Fragmentation: Research and Policy Implications of Polygon Discontiguity

By: Carlos Siordia and Amber Fox

Abstract: The American Community Survey (ACS) is created by the Unites States Census Bureau and contains the most recent and detailed information on the population. The U.S. Census Bureau releases Public Use Microdata Sample (PUMS) ACS files to allow public entities the ability to examine detailed individual-level data. In order to protect the confidentiality of survey participants, the Census only allows individual-level observations to be geographically referenced with Public Use Microdata Areas (PUMAs)—polygons that contain at least 100,000 people. Microdata files offer the unique advantage of creating custom tabulations on the population that are not made available elsewhere. The advantages from using PUMS files are limited by the typology of PUMAs. Our project fills a gap by introducing the reader to how PUMA typology is produced and how it affects research. The specific aim of this project is to highlight the fact that PUMAs can be fragmented—made up of physically non-adjacent/multi-part polygons. This is important because the treatment of fragmented/multi-part polygons as contiguous spatial entities erroneously imposes a false structure of contiguity that challenges theoretical and statistical assumptions in geographically aware research. By providing evidence from three metropolitan areas in Texas (USA) and displaying the degree of polygon discontiguity concentration by state, we outline some of the implications of polygon discontiguity for research and policy. We compliment our descriptive investigation by discussing solutions in closing and by identifying and discussing the three general elements in polygon fragmentation: quantity, distance, and size.