GEOCODING
What is geocoding? Geocoding is simply the process of taking addresses and associating them with their actual geographic coordinates on earth. This enables geospatial analysts to display specific addresses on a map and conduct various analyses on the addresses in association with other GIS data.
Problem
A business located in Raleigh North Carolina is trying to expand their customer base, and would like to start by identifying the distribution of current customers in Wake County. The company has provided current customer addresses, which can be geocoded to spatially analyze customer distribution. By geographically analyzing the locations of current customers, the business can identify areas with fewer customers to better target advertisements. The purpose of this project was to identify unrepresented areas in Wake County in order to strategize future advertisement campaigns.
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Analysis Procedures
The data used in this analysis included shapefiles of streets, zip codes, and boundaries in Wake County North Carolina, as well as current customer address information stored in tabular format. ArcMap (version 10.5) was used to display, manipulate, and analyze the data. First, the Wake County zip codes and customer information data to create a new address locator using the Output Address Locator tool. This was then used to geocode the customer addresses by zip code, resulting in a new shapefile containing only one point per ZIP code. This single point contained all of the customer addresses within that ZIP code. Some of the unmatched addresses were manually matched by correcting missing or incorrect data. For instance, certain addresses within the data table had incorrect or null values for the ZIP code. After correcting the data, a new address locator using the Wake County streets data was created and used to geocode the addresses by street. Again, some of the unmatched addresses were manually matched by correcting the address data.
Figure 1. Diagram of methods.
Results
The majority of the evaluation was solely visual. After geocoding by ZIP code, it became visually apparent that the resulting shapefile did not yield the desired results. This process simply demonstrated which ZIP codes had at least one customer, and the resulting map only had one point per ZIP code (Fig. 2). This was checked by looking at the attribute table and viewing the information for each point of the resulting shapefile. This visual analysis of the output led to geocoding the addresses a second time using the street addresses (Fig. 3), which clearly demonstrated the spatial distribution of customer addresses. From this map, one can easily discern that the majority of customers were located in the Raleigh and central Wake County areas, while few customers were at the extreme north and south regions of the county. This should be expected though, seeing as the population density is highest in the center of the county and is lower as you move further from Raleigh.
Figure 2. Map of customers geocoded by ZIP code.
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Figure 3. Map of customers geocoded by streets.
Application & Reflection
From this project, I learned how to use geocoding tools. Being able to map addresses provided in tabular format is a useful skill for any geospatial analyst.
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Problem Description: I am currently investigating precision agriculture technologies in my research, and geocoding could be extremely useful for my work. I am investigating the use of unmanned aerial systems (UAS) in scouting agricultural fields and monitoring plant health status. One major problem associated with this research is that much of it should be conducted at commercial farms, rather than controlled research facilities. Another extremely useful aspect that geocoding could be used for involves UAS flying regulations. Piloting UASs requires that operation is conducted at a certain distance away from airports and air fields.
Data Needed: Identifying locations I could potentially use the addresses of farmers to identify fields for data collection. This data is likely available from county GIS services, but a survey of farmers could also be conducted to determine field locations. Additional data, such as soil series data could be found through the national soil survey website.
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Analysis Procedures: To solve this spatial problem, I would first start by geocoding the addresses of farms of interest. After this, I would apply a buffer to the address points to ensure they are within a reasonable distance of North Carolina State University (within a ~2 hour drive). Next, I would identify airports within my area of interest, and apply buffers to these points to ensure farm addresses are not within 5 miles of the airports. Lastly, I could identify farm locations based on soil surveys, as sandy soil types are ideal for monitoring plant stress due to nutrient disorders, my main topic of interest.