Module 3: Comparing Projected Coordinate Systems

 

This week was focused on the introduction of projected coordinate systems. In this map, three different coordinate systems was used to display the same data, specifically counties in the state of Florida. This map is intended to compare the differences in data distortions for different coordinate systems. 

Data: 

A Florida County Boundary shapefile was downloaded from the online Florida Geographic Data Library. This shapefile was then re-projected in three different projected coordinate systems, Albers Conical Equal Area, NAD 1983 HARN State Plane Florida North FIPS 0903 (US Feet), and NAD 1983 UTM Zone 16N using the Project tool in ESRI ArcGIS Pro. 

Symbology: 

Four counties were selected: Alachua, Escambia, Miami-Dade, and Polk county. Each county was highlighted with a different color, while the counties that were not selected were set to white. 

Layout: 

The required map features learned from the previous week was also applied to this map (i.e. title, north arrow, legend, boundary, map creator, data source, and scale bar). A table was included to show the calculated area (square miles) for each county to quantitatively compare sizes based on each projected coordinate system.

Notes:

There are many ways to map data collected on a round earth on a flat map. Each must "stretch" or manipulate the data to flatten it, and it is best to choose the projected coordinate system that has the least amount of "stretching" in your map area. This is shown in the map table, as the calculated area varies for each county depending on the projection used. For example, Polk County is approximately 2010 square miles when using the Albers projection, but the area calculation is 12 square miles larger when using the UTM 16 N and only 3 square miles larger when using the State Plane N projection. The counties listed from most to least variation are Miami-Dade, Polk, Alachua, and Escambia. When comparing the projections area calculations, it seems that the Albers and the State Plane N projections are closer in area calculations than the UTM 16 N projection. This map shows that using consistent projections is important when comparing multiple datasets, as data is distorted differently for each projected coordinate system.