This tutorial consists of a collection of video modules where we look at examples of how to use the Missouri Census Data Center's Geocorr geographic web utility application. These are typical examples of the program's use ranging from easy to moderate in terms of difficulty. Note that these videos are rather large and may take a minute or two to load.
This example looks at a class use of the application in order to examine the relationship between two geographic layers, census tract, and ZIP code (ZCTA). We do it for an entire state, and then modify it to run for just a single county. The user is also shown the geographic glossary file link with a discussion of its utility.
Here we examine the correspondence of counties and CBSAs (metropolitan/micropolitan statistical areas) within a state. We do it first with the default 2000 census population as the weight variable and then demonstrate how how using the 2009 estimate as an alternative yields a report showing the latest (as of 2010, at least) population estimates for the county. Illustrates use of the geographic filtering section to tell geocorr to ignore areas not within any CBSA. Finally, we reverse the roles of the source and target geocode selections to get a report sorted by CBSA showing the component counties of each.
This example returns to Missouri and focuses on the point and distance options section of the form. We use the sample point suggested on the form (the coordinates of the St. Louis campus of the University of Missouri, located in St. Louis county), and look at school districts located within a 12-mile radius of this site. There are actually two examples in one here, with the first one just specifying a 12-mile radius as a way of selecting geography within that circle, and the second illustrating the use of something we call concentric ring pseudo-geocodes. The latter allows us to break down the school districts and their populations within a four-mile circle and two donut-shaped rings which provide coverage for the same 12-mile circle as used in the original example.
This example looks at six states and breaks them down according to their urban/rural portions. It does the same run with two different weight variables to demonstrate how a large majority of the population lives on a very small percentage of the land.