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14 min read

OGH Summer School Prague 2018

Author Tom Hengl
Published December 13, 2018

Dates: 19 – 25 August 2018
Location: Prague, Czech Republic

The IBOT, Prague 2018 Summer School (Sunday, August 19, 2018 to Saturday, August 25, 2018) was the 13th in a series of summer schools organized by R and Open Source (OS) GIS developers and enthusiasts. The 2018 theme was : spatial and spatio-temporal data analysis with R and OS GIS.

Playlist

30 Videos

Profile: Edzer Pebesma (IfGI University of Muenster, Muenster Germany)

5:57

Profile: Roger Bivand (Norwegian School of Economics, Bergen, Norway)

9:54

Profile: Markus Neteler (Mundialis, Bonn, Germany)

7:40

Profile: Chris Reudenbach (Philipps-Universität Marburg, Germany)

8:43

Profile: Tom Hengl (Envirometrix Ltd)

15:22

Profile: Hanna Meyer (Philipps University Marburg, Germany)

9:16

Profile: Jannes Münchow (GIS, Friedrich Schiller University Jena, Jena, Germany)

4:44

Profile: Jakub Nowosad

6:02

Profile: Matej Man (IBOT, Prague, Czech Republic)

5:49

Profile: Robin Lovelace (University of Leeds, UK)

8:40

Profile: Veronica Andreo (INMeT, Argentina)

6:15

Profile: Tim Appelhans (GfK Geomarketing, Germany)

7:20

Roger Bivand: "A practical history of R-sig-geo"

Roger Bivand: "A practical history of R-sig-geo"

44:26

Tom Hengl: "Machine Learning as a generic framework for spatial prediction"

Tom Hengl: "Machine Learning as a generic framework for spatial prediction"

51:39

Edzer Pebesma: "New R packages for spatial and spatiotemporal vector and raster data"

Edzer Pebesma: "New R packages for spatial and spatiotemporal vector and raster data"

1:26:04

Edzer Pebesma: "Simple features for R / tidy spatial analysis" practicals

Edzer Pebesma: "Simple features for R / tidy spatial analysis" practicals

1:07:25

Edzer Pebesma: "Scalable raster data analysis in the cloud with R"

Edzer Pebesma: "Scalable raster data analysis in the cloud with R"

56:04

Tomislav Hengl: "Computing with large rasters in R: tiling, parallelization, optimization"

Tomislav Hengl: "Computing with large rasters in R: tiling, parallelization, optimization"

1:19:50

Hanna Meyer: "Machine-learning based modelling of spatial and spatio-temporal data"

Hanna Meyer: "Machine-learning based modelling of spatial and spatio-temporal data"

53:25

Geomputation with R book

Geomputation with R book

26:27

Robin Lovelace: "Geocomputation with R"

Robin Lovelace: "Geocomputation with R"

58:46

Robin Lovelace: "Integrating spatial data in dplyr workflows: pitfalls and potential"

Robin Lovelace: "Integrating spatial data in dplyr workflows: pitfalls and potential"

1:13:28

Jannes Münchow: "The importance of spatial cross-validation in predictive modeling"

Jannes Münchow: "The importance of spatial cross-validation in predictive modeling"

1:23:29

Jannes Münchow: "R-GIS bridges: the examples of RQGIS and RSAGA"

Jannes Münchow: "R-GIS bridges: the examples of RQGIS and RSAGA"

43:07

Chris Reudenbach: "Link2GI - consistent linking of Open Source GIS with R"

Chris Reudenbach: "Link2GI - consistent linking of Open Source GIS with R"

1:06:37

Tim Appelhans: "Introduction to mapview and mapedit"

Tim Appelhans: "Introduction to mapview and mapedit"

32:46

Markus Neteler: "Analysing environmental data with GRASS GIS" (practicals)

Markus Neteler: "Analysing environmental data with GRASS GIS" (practicals)

1:25:38

Veronica Andreo: "Spatiotemporal data processing and visualization in GRASS GIS"

Veronica Andreo: "Spatiotemporal data processing and visualization in GRASS GIS"

1:25:14

Tomislav Hengl: "Mapping species distribution using Machine Learning"

Tomislav Hengl: "Mapping species distribution using Machine Learning"

1:25:30

Jakub Nowosad: "GeoPAT 2 - analysis of spatial and temporal patterns"

Jakub Nowosad: "GeoPAT 2 - analysis of spatial and temporal patterns"

1:20:18

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