This document discusses Todd Barr's background in GIS and spatial data consulting. It then provides information on R, including that it was developed in the 1990s based on S and S-Plus for statistical modeling. It discusses reasons to learn R, such as its community support, reproducibility, versatility, and ability to perform high-end analysis without economic barriers. Finally, it outlines R's use for spatial/GIS applications through libraries, interfaces with other software like ArcGIS and QGIS, visualization capabilities, and ability to create web-ready outputs.
3. Backround
• 20ish Years in GIS
• Worked with a Multitude of Agencies and International Non Profits
• Presented at Several Spatial, Data Science and Non Spatial
Conferences
• Lead Multi-Agency Strategic Planning Initiatives for Spatial Data Use
In Emergency Management
Was retweeted by ‘The Rock’ twice in one night
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7. BackgRound on R
• Developed in the 90s base on a Proprietary Statistical Language called
‘S’ and S-Plus, by Statisticians for Statistical Models.
10. Why LeaRn R
• Unleashes the Power of the Command Line Interface (CLI)
11. “With the advent of "Modern" GIS software, most people want to point and click their way
through life. That's good, but there is a tremendous amount of flexibility and power waiting
for you with the command line. Many times you can something on the command line in a
fraction of the time you can with a GUI.” - Sherman 2008, Desktop GIS p 283
"You get such a better understanding as to what you are doing with the geospatial analysis
functions when you type them in manually rather than using a wizard." - James Fee,
multiple years, and formats
29. R in Spatial/GIS
• Interfaces
• Spatial
• ArcGIS
• R interface supported by ESRI Open Project “R Bridge”
• QGIS
• Imbedded a Functionality
• Use R in the Native Script Editor
• GeoDA
• Native R code, and functionality
• gvSIG
• R plugin to allow
• Kinda Spatial
• Tableau
• Spotfire
• Capable of GeoAnalytics
• SAS
• SPSS