Module 6 - Scale Effect and Spatial Data Aggregation

    This week, in the sixth and final Special Topics in Geographic Science lab, was about Scale Effect and Spatial Data Aggregation.

    This weeks was broken into a few parts and has us analyzing scale and how it effects our data, as well as the aggregation of spatial data fore more governmental things such as gerrymandering. 

    So with the first part of the lab, we took data on hydrographic lines and polygons of a county and examined their lengths and details to one another. What we saw is that when the scale is increased, more detail and length is decreased. You can see this below in a screenshot from the lab where our highest scale, which is medium, is eclipsed in lengths as high goes father and the normal flowlines goes the farthest.

    The next part was more of the same where we analyzed a DEM layer and resamples it. In this part we started by changing the resolution by 1 then 2, 5, 10, 30 and 90 meters. What we saw is that the data's scale would slowly get more pixelated as we kept raising this scale until it was very blocky.

    The second part of the lab was more to do with aggregating data and comparing them to one another. As the first part of this lab had us examine the relationship between poverty and race in different geographic units. This was done with original block group and then with zip codes, housing voting districts, and counties. Once done we found that the trends were fairly similar even with different geographic units.

    The final part of the lab had out analyzing and looking at the gerrymandering with MAUP and how it aggerates the districts poorly. The main worst offender we found in the lab is shown below and we calculated this with Polsby-Popper Score. This part of the lab did not make much sense to me but I see that with MAUP is has caused some problems 

    

    Overall, this was a great last lab to utilize more GIS techniques in and I hope I am able to apply these into my future internship.

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