Title: Automated analysis of DEMs using R+OSGeo (workshop at Geomorphometry 2011)
Workshop moderators: Tomislav Hengl & Carlos Grohmann
Duration: 1 days
Room: University of Redlands Campus, Lewis Hall room 104
Intended aims and scope: This workshop aims at PhD students and professionals interested to use open source software packages for processing of their elevation data. R is the open-source version of the S language for statistical computing; SAGA (System for Automated Geoscientific Analyses) and GRASS (Geographic Resources Analysis Support System) are the two most used open-source desktop GIS for automated analysis of elevation data; Python is the programming environment increasignly used to automate DEM data analysis. The topics in this workshop will range from selection of grid cell size, choice of algorithms for DEM generation and filtering, to geostatistical simulations and error propagation. The workshop moderators will demonstrate that by combining R+SAGA/GRASS with other packages such as Python, "raster" and "maptools" R packages and GDAL utilities, we create a powerfull compo of tools capable of handling such demanding tasks as DEM generation from auxiliary maps, automated classification of landforms, and sub-grid parameterization of surface models.
For more info see the SAGA vs GRASS workshop (Zurich 2009).
Intended audience: PhD students and young DEM specialists. Anybody that would like to learn using R+OSGeo for DEM data analysis.
Day 1 (Introduction and first steps)
- 9:00-11:00 Introduction and software demo
- 11:00-13:00 Software installation and first steps
- 13:00-14:30 Lunch
- 14:30-15:00 Theoretical concepts (variograms, scales, spatial stats)
- 15:30-17:00 Hands-on-software exercises
For conference organizers
- A workshop room with 12-15 tables in U-shape (example);
- 8-10 extension cables with 20+ sockets for laptops;
- LCD projector and a large screen + whiteboard;
- WLAN-enabled laptop with Windows or Linux OS;
- R+OSGeo software (R, SAGA, GRASS, Python, FWTools, Google Earth) up and running;
- Some minimum knowledge or R and GRASS are recommended but not a prerequisite;
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