UNIVERSITY OF WISCONSIN - MADISON LIMNOLOGY SEMINAR Zoology 955 Spring Semester 2018
A limnologist’s introduction to spatial analysis and GIS in R
INSTRUCTOR: Dr. Hilary Dugan, Center for Limnology, Department of Integrative Biology, hdugan@wisc.edu Office hours by appointment.
CREDIT HOURS: 1 credit
MEETING TIME AND LOCATION: Tuesdays from 9:00-10:00 in Hasler Lab 210.
INSTRUCTIONAL MODE: Face-to-face. Zoom https://zoom.us/j/726741289
REQUISITES: Students should be familiar (beginner level) with the R programming language.
If you have never used R and would like to take this course, it does not take long to get acquainted. There are plenty of online courses (ex. https://www.coursera.org/learn/r-programming), and meaty text documents (https://cran.r-project.org/doc/manuals/R-intro.pdf). I highly recommend using RStudio as a code editor. RStudio provides a wealth of learning resources (https://www.rstudio.com/online-learning/#R), and handy desk cheatsheets (https://www.rstudio.com/resources/cheatsheets/).
COURSE STRUCTURE: This seminar will be tutorial based and focused on developing a skillset that can be applied in graduate student research.
COURSE DESCRIPTION AND OBJECTIVES: If you have never used GIS in your research, you may think of it as a great way of creating maps (and it is!). But more importantly, GIS is a good foundation for applying spatial analyses. As ecologists, much of our research has an inherent spatial component (sampling locations, species distributions, site heterogeneity). The objective of this course is to provide an introduction to handling and manipulation spatial data so that students can have the skillset and resources to apply spatial analyses in their own research.
This course will cover topics such as: handling spatial data, coordinates and projections, raster data sets (like climate or land cover data), data interrogation, modifying spatial data, maps, and the basics of satellite imagery. Even if you do not currently use spatial data in your research, it is advantageous to know how to complete simple GIS tasks. Both for your own research and your future career.
GRADING: Grades will be based on short assignments (25%), participating in class discussion (50%), and a final project based on individual research topics that will be presented during the final two weeks of the semester (25%). Numerical grades are assigned as follows: 93-100 (A), 88-92 (AB), 82-87 (B), 78-81 (BC).