In this week we worked on using scales, resolution on raster data and doing gerrymandering on congressional districts in the continental US. To start we did scale effects on vector data which I found to have a profound difference in how these were viewed.
The
more zoomed in the scale is that the geometric properties tend to decrease as
well. At least with the Count and total Perimeter. This were on a consistently
decreasing scale of values. The lengths were a bit different with the smallest
scale being the lowest length and the middle scale (valued at high) being the
largest length over the biggest scale (medium resolution). As well as the total
area which was a bit random in the numbers but the values were all relatively
the same with only minor differences based on scale.
Gerrymandering we used for the last part of this project and this is the effect that certain factors have on congressional districts. In essence it is defined as the odd shape and effect this has on these districts. So in here we did a couple things like viewing how some of these districts are broken up because they might have "island" parcels which distort their polygon shapes or basically if they are continuous polygons and if not then why. We also did a test for the compactness of these districts. This was the main part we focused on and the formula used to find this is called the Polsby-Popper Score which would be found in here by using this formula (12.56637 *! Area!) / (! Length! * 2).
We had a couple of outliers for sure but the worst one was in district 36 which will be listed in a screenshot below.
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