Geocoding Frac Sand Mines

Goal and Objectives:

The goal of this lab was to geocode a subset of frac sand mine locations in Wisconsin. This was to gain an understanding of data normalization and the accuracy of data collected by others.

Methods:

Before geocoding could occur, the addresses for the mines needed to be normalized (Figure 1). This involved adding additional columns to the excel spreadsheet, and copying different portions of the address field to them. This was done so the geocoder tool would be able to properly locate the mine's positions.

After all of the addresses were normalized, I added the excel sheet to the geocoding tool, and matched the fields to match the geocoding style. The geocoder then matched the addresses to their corresponding locations according to Esri's "World Geocoding Service". All of the addresses matched locations in the "World Geocoding Service", but weren't exactly accurate, so manual re-positioning of all of the points was necessary. In order to do this, the "address inspector" was used to "Unmatch" the point from its geocoded location, and the correct point was selected using the "Pick Address from Map" tool. Public Land Survey System (PLSS) information was used with the address information to identify the true locations of the mines.

Next, I compared my results to my colleagues. First, I used the "merge" tool to combine all of their shapefiles into one shapefile. I then used the "near" tool to determine the distances between each of my points and the closest point collected by my colleagues.

Results:

Figure  1: The table before normalization

Figure 2: The normalized table

The resulting table from the normalizing procedure was easier for the computer and persons to interpret (Figures 1,2) .

The initial geocoding results were extremely erroneous, with one of the initial results being located in Scotland, rather than its true location in Wisconsin (Figure 3).

Figure 3: One of the points was erroneously located in Scotland.

When comparing my results with those of my classmates, the differences between our resulting locations varied between 3 meters to 9 kilometers (Figure 4). 

Figure 4: A table showing the distances between my point locations
 and my classmates' point locations.

Discussion:

different types of errors
how can we know what points are correct?

Conclusion: