Scale and Spatial Data Aggregation

Resolution is more challenging to deduce using vector datasets rather than raster data representations.  With raster datasets, the resolution is determined by the size of the raster cell; vector data representations cannot be defined as easily.  Vector data is incredibly useful in illustrating objects with well known boundaries like roadways and lots of land.  Raster data can not only illustrate these types of features, but other continuous-field datasets like temperature and topography (Goodchild, 2011).  Of the latter, digital elevation models (DEMs) can be used to represent elevation and slope.  This and other types of continuous-field data can be captured using remote sensing technology and projected into DEMs at a resolution the size of the raster cell.

Gerrymandering is typically represented using vector data.  Borders in general are an arbitrary concept; the boundaries of congressional districts are no exception and are drawn with predispositions for political agendas.  However, gerrymandering is a testament to spatial analytics.  Though unfair, gerrymandering is the result of decades of improvement on GIS technology.  By intentionally drawing spatial boundaries determined by the attribute data of point features, political parties can all but assure electoral victories by excluding their opposition from within their districts.  These districts can be measured based on geometry (using compactness and contiguity) or based on the constituents of an area (Morgan & Evans, 2018).

In this exercise, I measured the compactness of US congressional districts by calculating the geometry of a created field in the polygon dataset.  By calculating a Posbly-Popper score of each polygon, square and rectangular polygons have a higher score than irregular polygons with a lower score.  By ordering the fields in ascending/descending order, you can identify the worse offenders as well as the most compact districts.

 

 

Goodchild, M.F. (2011). Scale in GIS: An Overview. Geomorphology. 130(1-2), p. 5-9. Elsevier.

DOI:10.1016/j.geomorph.2010.10.004

Morgan, J.D. and Evans, J. (2018). Aggregation of Spatial Entities and Legislative Redistricting. The

Geographic Information Science & Technology Body of Knowledge (3rd Quarter 2018 Edition), John P. Wilson (Ed.). DOI:10.22224/gistbok/2018.3.6