Geocoding

Strategies: I employed Esri’s ArcGIS Pro (Version 2.9) for this analysis using the following modules/tools; Excel to Table tool, Create Locator, Geocoding Address Tool, and Repair Geometry Tool. The coordinate projection for the primary input data for this analysis is the NAD 1983 State Plane North Carolina FIPS 3200 Feet. The data include (a) a polygon feature of Zip Codes in Wake County, (b) a polygon feature of Wake County boundary, (c) a line feature of Streets in Wake County, and (d) an excel table of customers’ addresses. The data for this analysis is obtained from the GIS520 Fall Semester Class (but originally from Wake County Open Data), and U.S. Postal Service’s ZIP Code Lookup. 

Methods: Geocoding involves matching addresses (pair of coordinates, zip codes, etc) in a table to a location on the earth’s surface. First of all, I geocoded the customer addresses using zip codes. I reviewed the attribute table of the zip code shapefile upon adding it to the map. I added the customer tabular data to the map using the excel to table tool. I use the create locator tool to create a locator where the 5-digit ZIP Code is the reference layer (Role = ZIP). I repaired the failed geometry error using the repair geometry tool with the repaired reference layer. Then, I rerun the create locator tool again. Next, I geocoded each of the customer’s addresses to a zip code (the zip code locator) using the Geocoding addresses tool. I reviewed the geocoded results and rematched some of the unmatched addresses after looking them up on the US Postal Service’s ZIP Code Lookup.

Secondly, I geocoded the customer addresses to their respective streets using the streets data. I used the create locator tool to create an address locator using the streets data as the reference layer and streets as the role. I set the multiple parameters (representing the industry standard for address data) under the field mapping to create the locator. I changed the geocoding options of the locator properties where the minimum match score is set to 85. I tested the locator by searching for an address within Wake county. After confirming that the locator is working, I geocoded the customer’s addresses to their respective locations using the geocode addresses tool. Additionally, instead of using a single field, I used multiple fields (Address or place, Address 2, City, Zip) for the geocoding using the customer address data as the reference layer. I reviewed the geocoded results and I rematched two (2) unmatched customer addresses using the rematch addresses tool. I exported three records from this result and I added labels to the three exported records.

Problem Description: One of the major problems of farmers in the rural settlements of Lagos state is the lack of mechanized equipment for crop production. Coupled with this is the lack of a comprehensive database with their locational information which limits the number of amenities provided to them by the government. Geocoding plays a crucial role in the management of information of an individual for identification and resource distribution. Therefore, the purpose of this analysis is to identify the spatial distribution of farmers in three farm settlements in Lagos state, Nigeria. This information will not just provide insight into their locations to the governments, but also enhance planning for proper allocation and equitable distribution of equipment among the farm settlements. 

Data Needed: A comprehensive street information to minimize the number of unmatched information. The data include (1) Street data (from the state GIS department) which includes House number, Streets, LGA/County, State, and Zip Code (2) Absolute location (i.e latitude and longitude) as well as the relative location which meets up with the industry standard of address data; and (2) Personal information (from survey) such as the type of farming activities they engaged in and the equipment needed.