Geographic Information Systems for Population Science Demography 5093/7093 Spring 2022
Wednesdays 6 - 8:15 PM Instructor: Dr. Corey S. Sparks Office hours: Wednesday afternoons, preferably by appointment corey.sparks@utsa.edu
This course is designed to give graduate students interested in social science, population science and policy fields a hands-on introduction to the use of Geographic Information Systems. The course will cover geographic data types, spatial data creation and management, exploratory spatial statistical analysis, and the basics of geospatial analysis. At the close of the course, students will be able to use R and QGIS to create and modify geographic data, perform descriptive analysis of spatial data and integrate and map data from various sources into the GIS environment.
We will be using R version (4.1) and Quantum GIS (QGIS) version 3.16 for this course. QGIS is open source and free and can be downloaded for windows or mac (OSX > 10.13) from here: https://qgis.org/en/site/forusers/download.html
We will also be using R. R is the language in which most research statisticians work and current methodological developments are being made, it is also free and can be used on any operating system.
Please update your R version (4.1) to the latest release and update all your packages. We will use R through Rstudio (https://www.rstudio.com/products/rstudio/download/) and we will use Rpubs for turning in all assignments.
You should also install the version 4.0 install of Rtools if you are a windows user. https://cran.r-project.org/bin/windows/Rtools/ For those of you interested in R, I have published all of the examples from this class, and my other classes to my Rpubs site: http://rpubs.com/corey_sparks, so you can follow along with that stuff if you choose.
I will also post data and other resources to my Github repository https://github.com/coreysparks/DEM7093
Copy and paste the following command in Rstudio to install the packages we will use in this class:
source("https://raw.githubusercontent.com/coreysparks/Rcode/master/install_first_7093.R")
In Rstudio. Please have these programs downloaded and installed prior to class.
There are two recommended books for this course:
-
Intro to R for Spatial Analysis & Mapping 2nd Edition (https://us.sagepub.com/en-us/nam/an-introduction-to-r-for-spatial-analysis-and-mapping/book258267 )
-
Learning QGIS, 4th edition. Packt Publishing (https://www.packtpub.com/big-data-and-business-intelligence/learning-qgis-third-edition)
I would also recommend downloading from the library
- Applied spatial data analysis with R 2nd edition from Springer Link (accessible through the UTSA library) (https://link.springer.com/book/10.1007%2F978-1-4614-7618-4)
and I also recommend consulting with this text for information on the tidyverse in R.
- R for Data Science (https://r4ds.had.co.nz/)
| Week | Date | Topic | Suggested Reading** Numbers refer to numbering of textbooks** |
|---|---|---|---|
| 1 | 1/19 | Class overview, Intro to software and class processes | 1 – ch 1; 2- ch 1 |
| 2 | 1/26 | Intro to QGIS | 2- ch 1 |
| 3 | 2/2 | Geographic data types, Getting data from the web | 1 – ch 3; 2- ch 2 |
| 4 | 2/9 | Data display and map creation In Class Lab | 1- ch 3 & 4 ; 2- ch 3 |
| 5 | 2/16 | Map projections and measuring distances | 2 – ch 2 |
| 6 | 2/23 | Data creation and editing In Class Lab | 2 - ch 2 |
| 7 | 3/2 | Geocoding | |
| 8 | 3/9 | Point pattern analysis Blog 1 Due | 1 – ch 5 &6 ; 2 ch 5 |
| 9 | 3/16 | No Class Spring Break | |
| 10 | 3/23 | Vector Analysis In Class Lab | 1 – ch 5 ; 2 ch 5 |
| 11 | 3/30 | Raster analysis | 2 ch 5 |
| 12 | 4/6 | Research Lab Day - No Lecture Blog 2 DUE | |
| 13 | 4/13 | Basic spatial statistics | 1 ch 7 & 8 |
| 14 | 4/20 | Basic spatial statistics In Class Lab Blog 3 DUE | 1 ch 7 & 8 |
| 15 | 4/27 | Research Lab Day - No Lecture | |
| 5 | 5/4 | Finals Period Final Blog Post 4 Due |