m.neteler's picture

LocationEM room

Objective: Introduction to GRASS GIS: from history and background to statistical modules and GRASS+R
General description: The tutorial will begin with a general introduction to GRASS with a few exercises to get familiar with GRASS. Emphasis will be put on some important concepts of GRASS: locations, computational regions and vector topology. The amount of exercises will then increase from session to session, ending with GRASS – R interaction.
Required back-ground knowledge: GIS and spatial data processing, statistics.
Software / R packages required: GRASS 6.4.2+ or 6.5, R.

9:00–10:30 GRASS GIS Intro, getting started - Markus Neteler
Summary: GRASS history and background; GRASS database concept (GISDBase, Location, Mapset); computational region in GRASS; raster format intro and principles of raster processing; vector format intro and principles of vector processing; data import/export; raster/vector reprojection. Exercises: data import/export, computational regions for raster processing, vector topological cleaning.

10:30–11:00 Coffee break;

11:00–12:30 Overview of the functionality in GRASS, exercises with selected modules - Markus Neteler
Summary: GRASS command structure; 3D visualisation; scripting in GRASS; statistical modules for raster maps, vector maps, and combining raster and vector maps. Each part will be accompanied by exercises.

12:30–14:00 Lunch break;

14:00–15:30 Lecture cont'ed + GRASS GIS exercises - Markus Neteler (in collaboration with Markus Metz)
Summary: GRASS - R interaction. Some analysis and visualization will be done with the ECA&D European climate data set from 1981 - 2010 (monthly aggregates)

15:30–15:45 Coffee break;

15:45–17:00 exercises -Markus Neteler (in collaboration with Markus Metz)
Summary: exercises continued; open analysis session.

Software download:

  • Course material incl. data sets download: here (updated!)
  • Software:
    • Linux: your distro may offer a recent GRASS GIS package, see also here
    • MS-Windows: get the latest 6.4.svn snapshot from here (corresponds to 6.4.3)
    • Mac OSX: get the package from here
    • R: get the package from here