The 2019 Summer School focussed on ‘Spatial and spatiotemporal computing: processing large-scale Earth observation data’, and was held at the University of Münster.
Dates: Sept 1 – 7, 2019
Location: Institute for Geoinformatics, Heisenbergstraße 2, 48149 Münster
The 2019 Summer School focussed on ‘Spatial and spatiotemporal computing: processing large-scale Earth observation data’, and was held at the University of Münster.
Analyzing large amounts of Earth Observation data with R and openEO
Not just R-spatial: sustaining open source geospatial software stacks / Data, data everywhere, nor any drop to analyse (without making brave assumptions about how the data represent underlying processes)
Computer graphics data structures for geo-spatial / Building a data library and R toolkit for domain-specific research group / Challenges of working with data in polar regions
Cloud based processing of geo and Earth observation data / Introduction to GRASS GIS / Advanced data analysis in GRASS GIS
Analysis of space-time satellite data for disease ecology applications with GRASS GIS and R stats / Analyzing space-time satellite data with GRASS GIS for environmental monitoring
Creating thematic maps in R (tmap package)
Machine learning strategies for spatio-temporal data
Analyzing movement data
Mastering machine learning for spatial prediction - overview and introduction in methods / model selection and interpretation, uncertainty
Assessment of global air pollution exposure
Processing Large Satellite Image Collections as Data Cubes with the gdalcubes R package
Dynamic modelling with PCRaster/python
