Week 5 - AppsGIS - Spatial Accessibility

This week we worked with Network Analyst in order to learn more about spatial accessibility modeling. For the first part of the assignment, we used some of the ESRI tutorials. These tutorials were very easy to follow, and made the process go smoothly. My only complaint is that it was annoying to have to go back and forth between windows trying to follow the directions. I have gotten used to using my tablet to read the lab instructions, while working on the lab on my laptop. Makes for a much easier time. Unfortunately, this is not an option when working through ArcGIS Help.

Additionally, we worked with data looking at hospital accessibility in Georgia. Much of the analysis was performed using the Join features followed by working in Excel. I have much more experience in Excel, but had not done much with data from ArcMap. Our results were primarily shown in either tables, or in Cumulative Distribution Functions (CDF), such as below:

Figure 1. Distance to nearest psych hospital, shown by age group. This graph shows
that more of the elderly population live farther from hospitals than those under 65.

 Finally, we used Network Analyst to look at spatial accessibility of community colleges in Travis County, Texas. We looked at the service areas of seven colleges in the area, with 5, 10, and 15 minute drive times. We first used the New Service Area function to set the colleges as facilities, and adjusted the settings so that the impedance was set to the time intervals. We solved the analysis to obtain a total of 21 service area polygons. This was repeated after removing one of the colleges from the data set, Cypress Creek Campus. The comparison resulted in the following:

Figure 2. Map showing the comparison of the service areas of the community
colleges of Travis County, Texas

We then used Closest Facility analysis to determine the closest facilities (colleges) to each of the census blocks. We again performed two analyses, one for all seven schools, and one for six schools (due to removal of Cypress Creek Campus). Luckily, you don't have to set up the parameters each time you want to run the analysis. After the analysis was performed, the tables were joined so that the information could be compared. We had to adjust the tables, though, as the FIPS code was not included in the tables of the Closest Facility analysis. Using Excel, the information in the completed table were analyzed to determine the spatial access for potential students in the area, before and after the closure of the college.

Looking at the attribute table, we had to select only those census blocks that were affected by the closure, and use the information within the attribute table to determine how they were impacted through changes in drive time. Lastly, we created a CDF of the information:

Figure 3. Resulting CDF for potential students affected by closure of Cypress Creek Campus.

I enjoyed learning about spatial accessibility this week, and feel that I am quite capable in this type of analysis. This clearly has many different potential applications in GIS analysis, and I am already thinking about how it can be used at my work.