Module 3.1: Scale Effect and Spatial Data Aggregation

     This final module explores the effects of scale and resolution differences on vector and raster data. We were given a data set of hydrographic vectors rendered at three different scales: 1:1200, 1:24000 and 1:100000. After exploring the dataset I found that larger scales such as 1:1200 can capture smaller details and finer geometric shapes better than smaller scales such as 1:24000 and 1:100000 since detail is lost as intricate features are simplified. These smaller scales can also cause small features to be completely excluded as the scale makes them comparably insignificant. 

    We also examined how the Modified Area Unit Problem (MAUP) can effect spatial data by using a nonwhite % vs. below poverty line % dataset as a case study. The data shows that the Scale Effect of the MAUP can cause results to vary if the units of analyses are differently sized spatial units (Zip Codes v.s. Counties, for example). The smaller the spatial scale, the more divergent the results can be.

     Lastly, we examined a map of the U.S. Congressional districts for gerrymandering. Gerrymandering is a political process in which a group in charge of redistricting draws districts in a way that would devalue an opposing group's vote. This can be done by clumsily clumping a target population's entire area into a single, messy district, resulting in them only winning one district. Another method of gerrymandering is done by drawing the districts in a way where the target population's area is heavily split up so their votes get drowned out by the other voters, resulting in them winning no districts.

 

     Pictured above is an example of one of the worst cases of gerrymandering in terms of compactness. Compactness is defined as the area a feature occupies in relation to its area center, an can be scored using the Polsby-Popper Score. This score is calculated using the formula 4π(Area)/(Perimeter)^2, resulting in scores between 0 and 1, where lower scores are considered bad. The district in the screenshot above achieved a very low score of 0.08.