This week we completed our final module for the Communicating in GIS course. We explored two new mapping techniques: Proportional Symbol and Bivariate Choropleth mapping. My map layouts and descriptions are below.
On the US Jobs map (above), I used transparent pink and yellow circle symbols to show the proportions of job increase and job decrease. For the nested legend, I used lines again to connect the legend symbols to the numerical labels. I made the connecting lines a dark gray to match the formatting in the rest of the map. I set each legend to show 4 values. I labeled each legend “Employment Increase” and Employment Decrease” respectively.
The bivariate map (posted above) is a creative and clear way to compare and
display two data variables on one map (Kimerling, et al. 2015). The data for
obesity and physical activity appeared to be very similar when the data was
assigned a graduated color symbology on the map. Without bivariate choropleth
mapping, it would be very difficult to display both variables on the same map.
By using bivariate symbology, we can clearly see the portions of the map where
meaningful data coincides – particularly in the lows and the highs. It's easiest
to tell where low inactivity and low obesity variables correspond throughout
the western portion of the continent. Conversely, it's clear to tell where high
inactivity and high obesity occur simultaneously in the south and southeastern
portions of the US. Bivariate mapping helps mapmaker to create meaningful maps
that can convey a large amount of data but can be understood quickly by the map
viewer.
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