Spatial Analysis with R

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

Meets weekly, 2017 Sep 3 to Oct 8, 18:15-20:45 Eastern Time (UTC-5)
Location: *Kendall ???? (first and last sessions) and online via
Blackboard Collaborate

*Sep 10 1. Intro to R bestiary 1, 2, 4
Sep 17 2. Points Redwoods 3.4.4, 6 1. Maps and stats
Sep 24 3. Polygon Montgomery County 2.4, 3.1-4  
Oct 1 4. Raster landsat 5.8-9 2. Point pattern
Oct 8 5. Graphs TBA 7  
*Oct 15 6. In-class presentations 3. Submit by Oct 6

Lee De Cola
DATA to Insight, Reston VA
Phone: 01-703-709-6972
hours: 10:00-18:00

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.


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


R language and particularly its spatial analysis tools.
Spreadsheet (e.g. Excel) often useful for restructuring data into R-readable formats.

PREREQUISITE: A course in statistics

TEXTS (you probably can rent these)

**Brunsdon, C. and L. Comber (2015) An introduction to R for spatial analysis & mapping Los Angeles, SAGE. The book covers a lot more material than we can, so i'll suggest sections that you should code.
Adler, J. (2010). R in a nutshell Sebastopol, CA, O'Reilly. There are many intro R books around; this is one I like.


*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.