[OSGeo Africa] Fwd: [OSGeo-Discuss] GEOSTAT course 15-22 June 2014, Bergen, Norway: registrations are now open!

Gavin Fleming gavinjfleming at gmail.com
Sat Feb 8 12:03:24 PST 2014


Hello all, and sorry for cross-posting,

let me forward the first announcement of the GEOSTAT 2014 Summer school.

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The GEOSTAT 2014 Summer School for PhD students and R-sig-geo
enthusiasts will be held this year at the Norwegian School of Economics
(NHH), Bergen, Norway in the period 15-22 June 2014 (arrive Sunday to
depart Sunday). The topics include: spatial and spatio-temporal data
and analysis in R, R as a GIS, spatial data modelling with raster
package, visualization of spatial and spatio-temporal data in Google
Earth, GRASS GIS and QGIS tutorials, and spatio-temporal geostatistics.

This summer school is limited to 50 participants (two parallel
sessions). Selection of candidates is based on a ranking system, which
is based on: time of registration, solidarity (participants further
away from the venue receive higher ranking), academic record, and
contributions to open source projects. The registration costs for the
summer school are typically between EUR 300 - 400; these cover the
actual costs, no profits are made. The organizers provide no
funding/scholarships to participants. Participants from ODA-listed
countries, however, can apply for a subsidized price for registration
costs.

To register for this summer school please visit the event homepage at:

http://www.geostat-course.org/Bergen_2014

The registration deadline is 1st March 2014.

Lecturers:

* Roger Bivand: Representing and handling spatial and spatio-temporal
data in R

* Robert Hijmans: Spatial modeling with environmental data (raster and
dismo packages)

* Edzer Pebesma: Spatial and spatio-temporal statistics with R: an
introduction

* Barry Rowlingson: QGIS + R tutorial

* Tomislav Hengl: plotKML tutorial (visualization of spatial and
spatio-temporal data from R to Google Earth)

* Markus Metz: GRASS GIS 7 tutorial / update

* Benedikt Gräler: Spatio-temporal geostatistics: choosing and fitting
models, interpolation (gstat tutorial)





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