Phil, You should look onto sp package which is the base for any other spatial packages in R http://cran.r-project.org/web/packages/sp/index.html
Also notice "Reverse depends" section where you can find a lot of useful packages for spatial operations and analysis. For loading shape files, "maptools", "rgdal" and similar packages will help you. You can read on-line "Applied Spatial Data Analysis with R" http://www.springerlink.com/content/978-0-387-78171-6#section=147788&page=1 which contains a lot of examples to work and analyze spatial data in R (the authors of the book are also the authors of "sp" and other spatial packages in R) Very important package is "rgeos" that contains all GIS functions: covers, intersects, inside, .... You can also find ideas in Clemens Reimann - Statistical Data Analysis Explained. Applied Environmental Statistics with R – 2008 (however it does not contain R code) >> Good morning, >> >> I am a student whom is currently working on a term project for my GIS >> Program. I am looking for a software package which can aid me in my >> project, >> and I was curious if R would be able to address my goals. >> >> My project includes power outage data from a hydro company (point data, >> with UTM coordinates attached), which is available in an Access database, >> or >> in a Shapefile. >> >> I would like to be able to take this poweroutage data, and then perform a >> spatial analysis of this data, perhaps as a hot-spot analysis, or in a >> points per raster square style analysis. >> >> With the completed analysis, I would like to be able to use an open source >> web mapping platform to display it for the 'company' I am performing this >> for as part of my project. >> >> >> Any insight you could provide me would be greatly, greatly appreciated. >> >> Thanks, >> >> Phil >> Kind regards, Antonio Rodriges ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
