Scale and Spatial Data Aggregation

In this week's lab, we looked at how scale and resolution can affect your data and analysis. 

In the first part of the lab, we looked at the same set of  hydrological data set at different scales. This showed us that the closer the scale, the higher the resolution, which means more data for any given area. For instance, the dataset with a scale of 1:1200 scale has the most detail for all features which included both polyline and polygon features that the other two maps do not have at all. The polylines and polygons had more detailed geometry than those from the dataset set at 1:100000.

Similarly, we saw in the second part of the lab that higher resolutions of raster data have more details. We were given a raster with 1m resolution of a mountainous area made from lidar data and processed it into various larger resolutions. As these numbers became bigger, the nuance of the landscape became more generalized. Moving from 1m resolution to 50m means that 50 pixels were combined into one larger pixel and averaged out. This resulted in a smoother raster with lower measurements of degrees. You can also see this in the imagery itself, going from a very detailed image at 1m to something that looks like it belongs in an 8bit video game by 50m.

In the last part of the lab, we assessed congressional districts for gerrymandering by assessing multipart districts and looking at the compactness of districts. Gerrymandering refers to drawing the boundaries of voting districts to achieve political advantage. In assessing the 14 multipart districts, I found 8 had justification for being multipart as they were all located along shorelines and the other parts represented nearby island. The other 6 to have no obvious reason for a multipart configuration. In looking at compactness, I use the Polsby-Popper test to calculate a rating based on the ratio of the area of the district to the area of a circle with the same perimeter. I found North Carolina's 12 had the lowest compactness score. North Carolina actually had 2/5 worst districts. 

The least compact district according to the Polsby-Popper score, North Carolina's 12th.