Data Cardinality

I used ArcGIS Pro 2.9.3 to solve this problem using geoprocessing tools of “Select by Attributes”, “Summary Statistics”, “Add Join”, and “Add Spatial Join”. There are four data files provided by the class, North Carolina General Assemble District, and ArcGIS.com, which are tabular data of the number of jobs created by companies, shapefiles of state house districts and senate districts, as well as layer package of USA ZIP code points.

First, I input all four data files into ArcGIS Pro. Then I checked the data format of zip codes in both the zip code points layer and the tabular data. Both layers contain text format of zip codes, which can be used as the field to join later. Then I used “Select by Attributes” for the zip code points layer for North Carolina only, and I exported the selected subset of the NC zip code points layer. Before joining the table and point layer, I used “Summary Statistics” to aggregate the number of jobs created in each zip code and exported the new table. Then I used “Add Join” to the zip code points layer with the new table that contains the sum of the number of jobs by connecting with the fields of zip codes. Then I used “Add Spatial Join” to the house district layer with the newly joined zip code points layer using a one-to-one join operation, intersect match option, and specifying the merging role as being the sum of the number of jobs. Finally, I created a map with graduated colors that represent the number of jobs created in each house district.

Similarly, for the process of joining data for the senate district layer, I used “Add Spatial Join” to the senate district layer with the zip code points layer, also using a one-to-one join operation, intersect match option, and specifying the merging role as being the sum of the number of jobs. Then, I created another map with the same color schemes of graduated colors that represents the number of jobs created in each senate district.

Using attributes join and spatial join are very useful tools that I have used for my own thesis research, and the skills learned from these tools can be applied in diverse fields of study. A possible scenario would be to explore the relationship between the number of houses sold for a given census tract and the species richness of birds to explore the “luxury effect” in Wake County.

Problem description: As a GIS specialist, I am asked to perform a tabular and a spatial join to integrate the layer of bird species richness and the layer that represents the number of houses sold.

Data needed: The data will be the Wake County census tract polygon layer, tabular data of the number of houses sold in Wake County census tracts provided by Zillow, and bird species richness data with GPS coordinates by a citizen science project, Triangle Bird Count.

Analysis procedures: I will first use “Add Join” to the census tract layer with the tabular data by connecting it with the fields of census tract IDs. Then I will add the bird data to the map as a points layer. Then I will use “Add Spatial Join” to the bird points layer with census tract layers by using the intersect match option and one-to-one join operation. Finally, I will be able to analyze the relationship between the number of houses sold and bird species richness.