Special Topics in GIS - M3.1 Scale Effect and Spatial Data Aggregation

 Scale determines the amount of data captured in spatial display, and as such it has direct effects on spatial properties of data. In both vector and raster data the smaller scale of measurement and the higher resolution, then the more data is available. 

On road polylines for example; roads and paths measured accurate to the nearest centimeter will contain much more data - more twists and odd jogs captured- than roads or walking paths measured to the nearest kilometer. In the kilometer scenario there may even be some paths excluded form the dataset altogether if they are under 0.5km in length. 

In a raster dataset this rule also holds true, but the effect of scale on spatial data is reflected more in the resolution -or cell size- of the raster. In rasters with large cell sizes less fine detail can be captured, so the data within each cell experiences an "averaging out" compared to rasters with smaller, finer resolution cells. This means that elevation properties like slope will decrease as the scale gets larger. This is not an inherently negative thing, as large scale and coarse resolution can be vital to displaying large areas in a short amount of time. It is important to keep in mind however how spatial properties can be manipulated by changing the scale and resolution of the data. 

Gerrymandering is one method used to manipulate data based on spatial properties. In this case the border of a voting district is drawn in such a way that the votes within it are more likely to be weighted in favor of certain demographics - even if those demographics don't make up the numerical majority of the area. By drawing the districts in these ways, representatives are effectively manipulating the scale of the votes in that area. Generally, districts that have been gerrymandered are not compact, and may divide communities or counties into different districts. By measuring compactness with a Polsby-Popper test (invented for paleontology and refined for politics by two lawyers in the 1990s) we can use area and perimeter to determine which districts are likely gerrymandered, and to what degree. 

During this analysis, I calculated the Polsby-Popper score for congressional districts in the continental Unites States, and highlighted those that were especially badly affected by a lack of compactness. 

This congressional district on the eastern seaboard is one of the worse "offenders" for not exhibiting compactness. The blue highlighted area outlines a district that wanders, doubles back on itself, and squeezes carefully in-between and around communities in order to manipulate scale of the votes in the district.