Any business opening a physical office or storefront needs to consider the characteristics of the area surrounding a proposed retail placement. Particularly relevant for retail placement is the location and the proximity to populated areas, public transportation, and city centers will impact the number of customers and, ultimately, the success of the business. Using publicly available data for a specific region of interest, Global Mapper can be used to analyze the area in order to determine the best possible locations for a new retail placement.
A retail store needs to be accessible to customers, and it needs to cater to the area in which it is situated. In an urban area, a dense population and proximity to public transportation hubs should be considered. On the other hand, a new location should not be too close to existing retailers in the same industry. Obviously, a new hardware store next to or in the same plaza as an established store may not garner as much business as a store in an area of the city that does not currently have a hardware store.
Existing Retail Locations
This study will focus on the process of determining optimal locations for a new hardware store in the city of Charlotte, North Carolina. To begin, a list of existing hardware stores is created, and their locations are loaded into Global Mapper to show the distribution across the city. Placing a new store location in an accessible, populated area that is in need of a hardware retailer will likely lead to business success.
The creation of a Voronoi diagram in Global Mapper breaks up the entire city area based on the existing hardware store locations. In this analysis, a polygon is created for each store to show the approximate area of influence. It is likely that consumers will go to the store located in the same polygon in which they live. Along the boundary between two or more polygons, multiple stores are equidistant. With this analysis, a likely spot for a new hardware store would be within a larger polygon area that does not have a centrally located store.
To show the approximate distance of travel to a local hardware store, range rings are created from each existing store location to approximate the symmetrical area of influence. Areas of the city covered by these circular polygons are areas currently being served by a community hardware store, and the overlap of multiple polygons indicates a highly served area. For a new hardware store location, it is the areas not covered by any circular polygons that are of the most interest.
The Spatial Operations tool finds the difference between the range ring features and city boundaries, indicating the areas where a hardware store is needed. These features will be used as the new candidate areas in the continuing analysis.
While customers are ultimately the most important factor for a retail location, the accessibility of the location and proximity to transportation infrastructure that help customers get to the store are important factors. Loading line features for major roadways and point features for public transit stops allow for a location accessibility assessment.
With public transit, most customers will need to walk from the bus or train station to reach the store location. A walkable distance, in this case, is considered a quarter-mile. To show this on the map, buffer features are generated for each public transit stop to represent the walkable area.
It can now be seen where the walkable areas overlap with major roadways that allow customers to travel by personal vehicle. Of course, the other set of features that needs to be taken into account are the previously identified candidate areas for a proposed store. Using the spatial operations scripting tool with two operations, a layer is first created to show the areas accessible from public transit and major roadways, and a second layer is then generated with polygons describing these accessible areas within the previously determined broad candidate areas.
Any retail location needs customers, and a higher population in an area means more potential customers for a store. Using TIGER/Line spatial data and US Census data, the population for the entirety of Mecklenburg County can be shown. The city area being considered is a portion of the county that cuts through various census tract polygons. Using the cropping tool in Global Mapper, the census areas can be cropped to retain only the portion within the city bounds.
To compute the modified population for the cropped census tracts, the new area for each polygon is measured, and a ratio of the modified area to the original tract area is used to compute an estimated population for the modified census tract polygons.
The population data for Charlotte is then classified and styled by the total population for the tract to show the overall population distribution. To measure the concentration of people per square mile, the attribute calculator is used again to standardize population by area, and the polygons are then styled by this calculated density value.
While total population is a good indication of how many potential customers are in an area, population density informs the concentration of potential customers. The population density attribute can be copied from the census tract areas to the candidate locations created by analyzing the existing hardware store locations and transportation methods. Since these candidate locations have already been determined to be accessible areas where a hardware store is needed, the areas can be styled by population density to rank them in order of suitability.
WORK MADE EASY WITH GLOBAL MAPPER
The tools available in Global Mapper With publicly available census and municipal data, along with a little research, Global Mapper is used to determine areas in need of a service or store and an ideal location for a proposed business. The new data layers generated in Global Mapper can be further analyzed, exported, or used as boundaries when searching for an empty storefront location for the proposed hardware store.
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