Database Cardinality in ArcGIS

10/02/14

Problem:

Elected officials from both Congressional chambers of the State of North Carolina require information pertaining to job creation in their districts. We were tasked with producing two maps showing the number of jobs created in each Senate district and in each House district from 2000 to 2001. The data used for these analyses were provided by Dr. Perver Baran, GIS instructor at NCSU, by the NCSU GIS library, and from ArcGIS.com. The data included a datasheet containing an industrial extension jobs survey of companies in North Carolina, spatial data pertaining to the congressional districts, and spatial data pertaining to the zipcode points for each zipcode area in the USA. The coordinate system for this project were NAD_1983_StatePlane_North_Carolina_FIPS_ 3200_Meters. To generate an accurate visualization of the features, the objective was to summarize the jobs number data, then perform tabular and spatial joins between the industrial survey data, the zipcode information, and the congressional district locations.

Analysis Procedure:

To put the files into the same scale, ArcCatalog was opened, and using the Extract Package tool, the LPK file was converted into a LYR file, then import into ArcMap and project coordinates into NAD_1983_ StatePlane_North_ Carolina_FIPS_3200_Meters. While in ArcCatalog, a new File Geodatabase was created. After importing the Zipcode, House, and Senate layers to ArcMap, Zipcode data specific to NC was selected and exported to a shapefile. It is important to ensure data are in the same format for linking and summarization. If they are not, perform data transformation to convert string values into numeric values or visa versa. The number of employees were summarized per zipcode, then joined via a tabular join to the zipcode points table to link them to spatial locations. This process enables the spatial join to align number of jobs created to the respective polygon data of the congressional districts. From these steps, maps could be generated for each of the chambers of NC Congress.

Figure 1. Workflow Diagram for Database Cardinality in ArcGIS

Results:

A good proportion of the State of North Carolina exhibited relatively meager job growth by House district (Figure 2) and by Senate district (Figure 3) between 2000 to 2001. The majority of job creation appeared to occur in the larger metropolitan areas.

Figure 2. Map of the number of jobs created per House District in North Carolina, 2002

Figure 3. Map of the number of jobs created per Senate District in North Carolina, 2002

Application and Reflection:

The data used in this exercise was driven by zipcodes, which is a powerful means of linking human demographics to human specific environmental parameters, such as spatial distribution. Gaining experience with where and how to obtain such demographic information was useful, but perhaps the most important lesson learned from these procedures was how to join data from another layer based on spatial location. This capability allows information to be summarized per specific area across a whole region of interest in one step. Returning to my daughters' mushroom identification project, we would like to keep track of and map our mushroom sightings along the trails of the parks in North Carolina. We are curious to know the spatial distribution of mushroom types vs. the local terrain and with respect to the time of year the sightings occur. Each of the mapped trail segments (see Our Mushroom Hunting) has coordinates and will be considered a unique polygon location. Each of the mushroom sightings will also have a GPS coordinate recorded at the time it is photographed. Using this cardinality technique appears to be an appropriate method to count the sightings, for instance on an annual basis, and offer some insight into which mushrooms are likely to be found in each hiking area and how their distributions may change over time. The data I would like to have for these analyses include the coordinates of the trail segments and the hiking area those segments are located, obtained from the map already generated, and the coordinates of the mushroom sightings, obtained at the time of the sightings. Each hiking area of Eno River State Park has a collection of trail segments. The mushroom sightings information might be joined to the trail location, then summarized and tied through spatial join to the hiking area they are found.