Spatial Analysis with R
Lee De Cola

Professional Seminar in Geospatial Technologies
GES 679-01
University of Maryland, Baltimore County
Department of Geography & Environmental Systems
The Universities at Shady Grove, Rockville MD

ldecola.net/edu/umbc/spatialR/syllabus_679.html

Meets weekly, 2018 Sep 3 to Oct 8, 18:15-20:30 Eastern Time (UTC-5)
Location: *Kendall 4212 (first and last sessions) and online via
Blackboard Collaborate

DATE TOPIC LAB TEXT **ASSIGNMENT
*Sep 10 1. Intro to R newhaven 1.1 - 2.4
  Sep 17 2. Polygons georgia 3.1 - 3.4, 4.5 1. due Sep 23
  Sep 24 3. Points tornados 3.4.4, 5.2 - 5.5, 6.1 - 6.5
  Oct 1 4. Grids volcano 3.4.6, 5.8 - 5.9 2. due Oct 7
  Oct 8 5. Geostats pennLC 7.1 - 7.6.1
*Oct 15 6. In-class presentations 3. due Oct 14
**Due before midnight on the indicated day.

LDECOLA@COMCAST.NET
DATA to Insight, Reston VA
Phone: 01-571-315-0577
hours: 10:00-18:00 EST (UTC–5)

OBJECTIVES – You will learn:

the R programming environment
about the mathematics of space
the fundamentals of spatial data structures
to do quantitative analysis of spatial processes
to conduct and present original research

COURSE ACTIVITIES

Real-time lab exercises using R interactively and collaboratively
Readings and significant coding exercises
Three assignments, including a final project presented in the last session

SOFTWARE

R language and particularly its spatial analysis tools.
NOTE: Priddy Librarian Amy Trost is offering Intro to R workshops on 2018 Sep 4 at 1600 and Sep 24 at 1230.
Spreadsheet (e.g. Excel) often useful for restructuring data into R-readable formats.

PREREQUISITE: A course in statistics

TEXT

REQUIRED: Brunsdon, C. and L. Comber (2015) An introduction to R for spatial analysis & mapping Los Angeles, SAGE. The syllabus table above shows the relevant (sub)sections, but as the book covers a lot more material than we can, i'll suggest the pages that you should code yourself.
RECOMMENDED: Adler, J. (2010). R in a nutshell Sebastopol, CA, O'Reilly. There are many intro R books around; this is one I like.

REFERENCES

Bivand, Roger, et al. (2013) Applied spatial data analysis with R New York, Springer. An excellent but quite technical review of our topics.
Waller, L. A. and C. A. Gotway (2004) Applied spatial statistics for public health data Hoboken, N.J, John Wiley & Sons.
Cressie, N. A. C. (1991) Statistics for spatial data New York, Wiley.