Exercise 6 - Data Normalization, Geocoding, & Error Assessment

Introduction - In this exercise we used data from a excel spreadsheet and normalize the data. We then learned how to geocode the data and assess our errors based on our classmates results. The data we were using was addresses of sand mines in Wisconsin for our semester long project on frac sand mining in Wisconsin.

Methods - We first tried to geocode the data using ERSI ArcGIS Online's World Geocode Service. However, since our data wasn't normalized we weren't able geocode any of the addresses. So, we normalized the data by finding the addresses, zip codes, and town for each mine. Many of the sand mines had PLSS addresses so we had to use a school server to find street addresses for those mines that didn't have one. Once we had the data normalized we were able to successfully geocode the address using the World Geocode Service.

Results - Once we geocoded the sand mine locations we were able to map them out in ArcGIS.

The original data before normalization

The data after normalization, ready for geocoding

Map of the geocoded sand mine locations in Wisconsin

Each of us in the class was given about 20 mines to geocode and at the end of the exercise we compared our geocoded mines with those of classmate's who had the same mines. Below is a table of the mines that I geocoded, their name and the distance from my classmate's geocoded location of the same mine.

Mine ID	Facility Name	Distance of my geocoded location from closest classmate's (rounded to the nearest meter)
109	MIDWEST FRAC AND SANDS	0
111	SIOUX CREEK SILICA	0
125	RIVER VALLEY SANDS	14313
136	MUSKIE PROPPANTS	0
138	PREFERRED SANDS	0
151	FG MINERALS (WISCONSIN INDUSTRIAL SAND)	0
152	FG MINERALS LLC	0
163	ATLAS RESIN PROPPANTS, LLC	11383
165	BADGER MINING CORP-TAYLOR PLANT	10603
178	TOWN OF BROCKWAY MINE	0
179	WESTAR PROPPANTS LLC	246
190	BLACK CREEK LIMESTONE CO	3044
192	DIAMOND BLUFF INDUSTRIAL SAND	239
205	ARCARDIA SAND CO	0
206	D95 NORTH SITE - SPARTAN SAND, LLC	1614
218	PATZNER SAND PIT	0
219	PREFERRED SANDS OF WISCONSIN, LLC	2920
232	VERNON BUE SAND MINE	4850
233	FML SAND - READFIELD	3187
245	NORTHERN FRAC SAND LLC	604
246	CHOPPER FARMS	128

Discussion - My data and my classmates' data have low positional accuracy due the uncertainty of certain address were we had rely on PLSS interpretation in order to assign an address to some of the sand mines. There is a inherent error in the data automation and compilation. In some cases there is no knowing which location is correct, however in other cases which show large differences in the data you can see that one or the other point is more accurate based on the PLSS address.

Conclusion - It isn't easy to normalize and geocode addresses especially with a PLSS address instead of a street address.