Date of Award

Spring 5-1-2018

Degree Type

Masters Thesis

Degree Name

Master of Science (MS)


Geography and Geology

Committee Chair

David H. Holt

Committee Chair Department

Geography and Geology

Committee Member 2

David M. Cochran

Committee Member 2 Department

Geography and Geology

Committee Member 3

George T. Raber

Committee Member 3 Department

Geography and Geology


Point location using geographic information systems (GIS) technology has become integrated into everyday society and daily decision-making by utilizing addresses to provide goods and services. A need exists at a national, state, and local level for an address database. The objectives of this study were to [1] determine the most suitable address data model to be used in Mississippi, [2] determine how positional accuracy changes between urban and rural areas, and [3] determine spatial variations in aerial imagery. Address data model comparisons were conducted using match rates between street, parcel, and point address models. Positional accuracy was determined for urban and rural areas using GPS points and margin of error. A mean center and standard distance calculation were performed using one standard deviation. [1] The point address data model (93% matched) and parcel data model (93% matched) outperformed the street data model (06%). [2] The results show that 65% of the average mean points fell within 13 feet – 38 feet from the structure. The average distance from mean was 27.87 feet in urban areas and 82.98 feet in rural areas [3] 75% of the total points fell within the margin of error in urban areas and 80% of the total points in rural areas.

Match rates were influenced by both the quality of reference and input address datasets. Using an average point location is acceptable for addressing in urban and rural areas. There was no significant shift or change between the 2006 and 2015 imageries. Address collection using the point address data model and high-resolution aerial imagery is an accurate, cost-efficient way to build an address database.