Links and slides from GEOSTAT2018
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README.md

GEOSTAT 2018 - links and slides

Monday

Roger Bivand: “A practical history of R-sig-geo”

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

Tim Appelhans: "Introduction to mapview and mapedit"

Robin Lovelace: “Geocomputation with R”

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

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

Tuesday

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

Tim Appelhans: “Using mapview and mapedit to visualise and edit geo-spatial data interactively in R”

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

Jianghao Wang: Urban Sensing and Computing - Big Data Analytic with Open Source Software

Wednesday

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

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

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

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

Robin Lovelace, Jakub Nowosad, Jannes Münchow: "Geocomputation with R - book unlaunch"

Thursday

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

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

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

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

Friday

Tomislav Hengl: "Mapping species distribution using Machine Learning"

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

Roger Bivand: "Process scale and autocorrelation"

Interviews

Additional links