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
|*Sep 10||1. Intro to R||
||1.1 - 2.4
|Sep 17||2. Polygons||
||3.1 - 3.4, 4.5||1. due Sep 23|
|Sep 24||3. Points||
||3.4.4, 5.2 - 5.5, 6.1 - 6.5|
|Oct 1||4. Raster||
||3.4.6, 5.8 - 5.9||2. due Oct 7|
|Oct 8||5. Graphs||
|*Oct 15||6. In-class presentations||3. due Oct 14|
Lee De Cola
DATA to Insight, Reston VA
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
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
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.
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.
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.