OpenGeoHub Summer School 2020 (Wageningen International Conference Centre, Aug 16–23, 2020)

[Madlene Nussbaum]

Liebe alle

Wer mit Geodaten und R oder freier GIS-Software allgemein arbeitet, der soll sich doch
eine Weiterbildung in den Niederlanden überlegen.

Die Summer School ist eine lebendige Sache mit Teilnehmenden aus verschiedensten Gebieten.
Entwickler*innen von R-Packages oder anderer freier GIS-Software sind jeweils da und
bieten Module an. Das meiste ist stark auf die Anwendung ausgerichtet mit Code-Beispielen,
Übungen, Live-Demos etc.

Die Anmeldezahl ist limitiert, deshalb gibt es ein Auswahlverfahen. Ich kann jemanden als
"Wildcard" einladen, diese Person wird auf jeden Fall teilnehmen können. Bei Interesse
bitte offiziell anmelden und mir mitteilen, damit ich es melden kann.


Liebe Grüsse,
Madlene





-------- Forwarded Message --------
Subject: [Pedometrics] OpenGeoHub Summer School 2020 (Wageningen International Conference
Centre, Aug 16–23, 2020)
Date: Tue, 26 Nov 2019 10:29:34 +0100
From: Tomislav Hengl <tom.hengl at gmail.com>
To: Pedometrics at mailman.sydney.edu.au <Pedometrics at mailman.sydney.edu.au>


This is the first announcement for the OpenGeoHub Summer School 2020 that will be held at
the Wageningen Int. Conference Centre (Hotel and Conference centre) in the period Aug
16–23, 2020. The registrationsare now open. For more info see:

https://opengeohub.org/summer_school_2020

The special theme of the Summer School 2020 is:

"Developing Machine Learning Algorithms for spatial and spatiotemporal data science problems"

Lecturers/topics (sorted alphabetically):
- Christian Knoth: "Introduction to Deep Learning in R for the analysis of UAV-based
remote sensing data"		
- Dainius Masiliunas: "Global-scale land cover mapping using FOSS4G"
- Dainius Masiliunas: "OpenEO demo (R client)"
- Dainius Masiliunas: "Detection of breaks in time series using the 'bfast' package in R"
- Dylan Beaudette: "Algorithms for Quantitative Pedology: R packages for working with
soils data at scale"
- Dylan Beaudette: "High performance vector data analysis delivery with PostGIS"
- Dylan Beaudette: "Credible metrics for determining similarity, accuracy, and precision
in the context of soil type mapping"
- Edzer Pebesma: "Handling and analysing vector and raster data cubes with R"		
- Giuseppe Amatulli: "GDAL/OGR and PKTOOLS for massive raster/vector operations"		
- Hanna Meyer: "Machine learning in remote sensing applications"		
- John E. Lewis: "Spatial mixed models & semiparametric regression"
- John E. Lewis: "Working with and the modelling of temporal data"
- John E. Lewis: "Using R for machine learning modelling - a coding introduction"
- Julia Wagemann: "Analysis of Big Earth Data with Jupyter Notebooks"
- Julia Wagemann: "Dashboarding with Jupyter Notebooks and Voila"	
- Longzhu Shen: "Predictive modeling of nitrogen distributions in US streams in a machine
learning framework"		
- Madlene Nussbaum: "Mastering machine learning for spatial prediction I - overview and
introduction in methods"
- Madlene Nussbaum: "Mastering machine learning for spatial prediction II - model
selection and interpretation, uncertainty"	
- Marius Appel: "Creating and Analyzing Multi-Variable Earth Observation Data Cubes in R"		
- Meng Lu: "Assessment of global air pollution exposure"		
- Paula Moraga: "Spatial modeling and interactive visualization with the R-INLA package"		
- Richard Barnes: "High-performance geocomputing for hydrological / terrain modeling"
- Richard Barnes: "Leveraging Python, clusters, and GPUs for geocomputation"
- Richard Barnes: "Reproducible scientific analysis"
- Tim Appelhans: "mapview package tutorial"		
- Tomislav Hengl: "Automated predictive mapping using Ensemble Machine Learning"
- Tomislav Hengl: "A step-by-step tutorial to optimization of geocomputing (tiling and
parallelization) with R"

Important dates:
- 26th of November 2019 — registrations open,
- 1st of February 2020 — registrations close,
- 16th of February 2020 — selection of candidates and invitation letters sent,
- 12th of April 2020 — course fee payment deadline,
- 1st of May 2020 — official programme published,
- 16 August to 22 August 2020 — Summer School,

The Summer School is limited to 70 participants. In the case of higher number of
applications, candidates will be selected based on a ranking system, which is based on:
time of registration, solidarity, academic output and contributions to the open source
projects. The final programme of the Summer School will shaped interactively.

Course fees:
The registrations fees for this Summer School full course fee will be in the range 400–500
EUR (exact number will be provided in the invitation letter). Participants from ODA
countries (employed by an organization or company in ODA-listed country) and/or full-time
students (not under work contract as University assistant or similar) have a right on
reduced fee (usually 40% lower than the full registration fee).

Summer School is organized on a cost-recovery basis. OpenGeoHub foundation is a
not-for-profit research foundation located in the Netherlands. All lecturers are
volunteers. None of the lecturers receives any honorarium payment or is contracted by the
local organizers.

Come to Wageningen the town of Life Science and improve your coding / geocomputing skills!

Follow us:
https://twitter.com/opengeohub
https://www.youtube.com/c/OpenGeoHubFoundation
https://business.facebook.com/Opengeohub-foundation-274552396602535/

-- 
T. (Tom) Hengl
Technical support / Vice Chair
The OpenGeoHub Foundation
Mail: OpenGeoHub Foundation, Agro Business Park 10, 6708PW Wageningen, NL
Tel: +31 (0)317 427537
Url: https://opengeohub.org/about
skype:tom.hengl?chat