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GEOSTAT tutorials

GEOSTAT software

Software iconList of FOSS software used in this course and installation instructions. Follow these instructions to prepare and customize the software before the beginning of the course.

Literature used

ASDAR bookList of books / lecture notes used in this course. See also: CRAN Task View: Analysis of Spatial Data.


« February 2017 »

GEOSTAT at Geoscience Australia

11 Apr 2011 09:00
16 Apr 2011 17:00


Spark-Helmore Theatre
The Australian National University
35° 16' 49.008" S, 149° 7' 8.472" E


Course/workshop organizers:

  • Augusto Sanabria, Geospatial & Earth Monitoring Division Geoscience Australia
  • Alan Welsh, Centre for Mathematics & Its Applications. Australian National University

Objectives: Introduce participants to open source tools R+OSGeo, give some hands-on training and provide enough resources (literature, examples, datasets) so that participants can continue developing his/her skills independently. At the end of the workshop each participant will be familiar with how to load spatio-temporal data in R, reformat and analyze it, visualize it using Open Source GIS and Google Earth and write results in various formats. We also aim we also aim at getting Australian/NZ scientists more involved in the R+OSGeo activities (both as users and contributors).

Target group: Australian/NZ scientists that use Spatial Data Analysis in their work but are not GIS specialists or spatial statisticians; various backgrounds (economists, engineers, scientists, mathematical modellers, etc.).


Course moderators:

  1. Tomislav Hengl (Tom), Senior research, ISRIC - World Soil Information, Wageningen University
  2. Dylan E. Beaudette (Dylan), Soil Scientist - Natural Resources Conservation Service, USDA

Guest lectures:

  1. John Maindonald, Centre for Mathematics & Its Applications, Australian National University, Canberra
  2. Graham Williams, Senior director and Chief Data Miner, Australian Taxation Office, Canberra

Daily programme

Coffee breaks daily at 10:30 and 15:30

DAY1: Introduction and software installation

  • 9:30 - 10:30 Welcome note and course overview [PDF] (Hengl & Beaudette)
  • 11:00 - 13:00 Introduction, Research Interests, OSGEO Demos [PDF] (Beaudette)
  • 14:00 - 15:30 Software installation and first steps (Hengl & Beaudette)
  • 16:00 - 18:00 Open Source GIS (OSGEO) [PDF] Demonstrations (Beaudette)
  • (optional) 18:00 - 19:30 First steps in R (Hengl)

DAY2: Space-time data formats (field observations)

  • 9:00 - 11:00 Working with Spatial and Time-Series Data in R [PDF] (Beaudette)
  • 11:00 - 13:00 Visualization of Spatial and Time-Series Data in R (Beaudette)
  • 14:00 - 17:00 Exercise: Time-series of meteorological measurements (Hengl)
  • 17:00 - 17:30 Discussion block (Hengl, Beaudette)

DAY3: Working with gridded maps

  • 9:00 - 11:00 Introduction to spatial db / SQL and PostGIS [PDF] (Beaudette)
  • 11:00 - 13:00 GRASS GIS, R+FWTools, SAGA GIS [PDF] (Hengl)
  • 14:00 - 15:30 Exercise: Preparation of gridded maps for the HRtemp2008 case study [MODIS images] (Hengl)
  • 16:00 - 17:30 Guest lecture by Graham Williams: "FOSS in industry"

DAY4: Spatial prediction

  • 9:00 - 11:00 Overview of spatial prediction models [PDF] (Hengl)
  • 11:00-13:00 Regression-kriging (Hengl)
  • 14:00 - 17:00 Exercise: spatio-temporal interpolation of daily temperatures (Hengl)
  • 17:00 - 17:30 Discussion block (Hengl, Beaudette)
  • +20:00 Dinner at the Indian restaurant close to ANU

DAY5: Visualization of space-time data using Google Earth (P.A.P. Moran room! building 26b located in map GH32 at grid reference G3)

  • 9:00 - 10:30 Guest lecture by John Maindonald: "Linear models in spatial statistics" [PDFadditional materials
  • 11:00-13:00 Visualization of space-time data in Google Earth (Beaudette)
  • 14:00 - 15:30 Open block
  • 16:00 - 17:00 Discussion forum: where do we go from here?

DAY6: Excursion (optional)

Case studies:

  1. HRclim2008: Daily temperature measurements (365 x 159 locations)
  2. Meuse: Soil samples in the southern Netherlands

Key literature:

Requirements and preparation

Each participant is expected to come with his/her own WLAN-enabled laptop. Each participant is responsible for maintaining and customizing the software. Software to be used at the course (installation in detail):

 How to prepare for this course?

  1. Study the recommended literature and web-sources.
  2. Install and test using recommended software.
  3. Obtain the case studies and try to import and visualize data.



Welcome note and course overview3.22 MB
Working with Spatial and Time-Series Data in R1.17 MB
GIS analysis in R+OSGeo2.04 MB
A Practical Guide to Geostatistical Mapping4.12 MB
Dylan | Day 1 | Introduction13.07 MB
Dylan | Day 2 | OSGeo demo7.21 MB
Dylan | Day 2 | Space/Time R-Fu861.11 KB
Tom | Day 3| Modis hdf images14.08 MB
Dylan | Day 3 | PostGIS Introduction1.88 MB
spgrass6_and_pgsql.R731 bytes
Dylan | Day 3 | GRASS GIS Demo5.64 MB
Dylan | Day 5 | Basic Notes on Getting Data into Google Earth113.35 KB
ov_Maindonald_spatial.pdf582.49 KB
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Comments (9)

Writing Custom Panel Functions in R

As I mentioned in class, it can be quite useful to extend the basic functionality of lattice graphics using 'custom panel' functions. Here are a couple of self-contained demos that illustrate several types of different custom panel functions.


R Package for Geochemists

Geochemists in the course may be interested in the 'CHNOSZ' [1] package for R. From the project webpage:
"This package includes functions and data sets to support chemical thermodynamic modeling in biochemistry and low-temperature geochemistry. The features include calculation of the standard molal thermodynamic properties and chemical affinities of reactions involving minerals and/or biomolecules; a database of thermodynamic properties of aqueous, crystalline and gaseous species; amino acid group additivity for the standard molal thermodynamic properties of neutral and ionized proteins; use of the revised Helgeson-Kirkham-Flowers equations of state for aqueous species; construction of equilibrium activity diagrams as a function of temperature, pressure, and chemical activities or fugacities of basis species."

Definitive Guide to PostGIS

This recently published book [1] is probably the best introduction, reference, and cook-book for all things related to PostGIS. There are several way to get the book, either as a printed volume or as a searchable PDF. Highly recommended.


Interesting Link Between Qgis -- R: ManageR

Pierre just pointed out an excellent tool for linking spatial data between QGIS and R. Very slick user interface, based on python (i.e. multiplatform), and open source.

Mezogis: Graphical Interface to PostGIS

Rattle Interface to Common Statistical Operations in R

Quick follow-up from yesterday's talk by Graham Williams, regarding his rattle package. Documentation, discussion, and installation instructions can be found here:


An excellent resource for getting started in GRASS, please be sure to check out the GRASS Wiki.

Raster Warping Examples

Take a look at this page [1] for an example of how different raster warping algorithms affect the resulting map, and derived maps.

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