OpenGeoHub Summer School 2023

Alexander Brenning

I’m a full professor of geographic information science in the Department of Geography of Friedrich Schiller University Jena, Germany. My research interests include geospatial modeling of Earth surface processes, machine learning, natural hazards, and remote-sensing data analysis. I enjoy contributing to the open-source data analysis ecosystem of with my geocomputing-related packages.

  • Spatial ML model assessment and interpretation (part 1)
  • Spatial ML model assessment and interpretation (part 2)
Alicja Balfanz

I am part of the Environmental Informatics Team at Brockmann Consult GmbH. Brockmann Consult GmbH develops software for the exploitation of environmental data from Earth Observation and other sources, provides information and consultancy services to businesses, public institutions, and national as well as intergovernmental agencies.

  • xcube for spatiotemporal data analysis and visualization (part 1)
  • xcube for spatiotemporal data analysis and visualization (part 2)
Anita Graser

Anita Graser in an expert in spatial data science for mobility and transport applications. She graduated with an MSc in Information Technology specializing in Geomatics in 2010 and received her PhD in Applied Geoinformatics from the University of Salzburg in 2021. Since 2007, she works in applied research at the AIT, focusing on spatial analysis of transport and movement data. Furthermore, Anita currently teaches at UNIGIS Salzburg, serves on the project steering committees of the open-source projects QGIS and MobilityDB, and is the lead developer of the open-source software library MovingPandas. She is an internationally sought-after speaker, has published more than 40 scientific articles, and several books. In 2020, she has been awarded the international OSGeo Sol Katz award for her contributions to open-source geographic information systems as well as the national Futurezone Women in Tech Award.

  • Data engineering for Mobility Data Science (with Python and DVC)
Anna Petrasova

Anna is a geospatial research software engineer with PhD in Geospatial Analytics. She develops spatio-temporal models of urbanization and pest spread across landscape. As a member of the OSGeo Foundation and the GRASS GIS Project Steering Committee, Anna advocates the use of open source software in research and education.

  • Parallelization of geoprocessing workflows in GRASS GIS and Python (part 1)
Caitlin Haedrich

Caitlin is a 3rd year doctoral student in the GeoForAll Lab at North Carolina State University in Raleigh, NC, USA. She has been working on improving the integration of GRASS GIS and Jupyter Notebooks.

  • Parallelization of geoprocessing workflows in GRASS GIS and Python (part 1)
  • Parallelization of geoprocessing workflows in GRASS GIS and Python (part 2)
Edzer Pebesma

Affiliation: University of Münster
Research interests: Spatial Statistics, Geoinformatics, Spatial Data Science, Reproducible Research, R
About: I lead the spatio-temporal modelling laboratory at the institute for geoinformatics, and am currently head of institute.

  • Raster and vector data cubes in R (part 1)
  • Cloud-based analysis of Earth Observation data using openEO Platform, R and Python (part 1)
  • Raster and vector data cubes in R (part 2)
  • Cloud-based analysis of Earth Observation data using openEO Platform, R and Python (part 2)
Ewa Grabska-Szwagrzyk

I am a geographer with a PhD specializing in remote sensing analysis of forests & R enthusiast.

  • Environmental analysis using satellite image time series (part 1)
  • Environmental analysis using satellite image time series (part 2)
Jakub Nowosad
  • Sharing your geospatial knowledge in the open
Jarek Jasiewicz

Graduate in geology from the Adam Mickiewicz University in Poznan (Ph.D 2000). Works on computer vision of geospatial data and geospatial machine learning, author of dozens of publications. Researcher and head of the Laboratory of Applied Geoinformatics.

  • Mapping explanation - Python toolchaing for spatial interpretative machine learning (part 1)
  • Mapping explanation - Python toolchaing for spatial interpretative machine learning (part 2)
Krzysztof Dyba

I am a PhD student in the field of Earth and environmental sciences at the Adam Mickiewicz University in Poznań. I am interested in spatial data analysis, remote sensing and programming in R, particularly in agriculture, and I was involved in several R&D projects related to crop classification, yield prediction, and soil mapping. I also contributed to the development of R-spatial packages.

  • Unsupervised classification (clustering) of satellite images (part 1)
  • Hackathons (consultations)
  • Unsupervised classification (clustering) of satellite images (part 2)
  • Hackathon workshop
  • Announcement of the hackathons winners
Lorena Abad

I am a PhD candidate at the Geoinformatics Department of the University of Salzburg. I focus on bigEO and remote sensing analysis for landscape dynamics and geomorphological applications. I have worked with FOSS4G for my research focusing on Sentinel products. I really like biking and hiking in my spare time :)

  • Tools and packages to query and process Sentinel-1 and Sentinel-2 data with R and Python (part 1)
  • Tools and packages to query and process Sentinel-1 and Sentinel-2 data with R and Python (part 2)
Maarten Pronk

GeoData Scientist at Deltares

  • Processing geospatial data using JuliaGeo framework (Julia tutorial) (part 1)
  • Processing geospatial data using JuliaGeo framework (Julia tutorial) (part 2)
Michael Dorman

Michael Dorman is a programmer (since 2016) and lecturer (since 2013) at the Department of Geography and Environmental Development, Ben-Gurion University of the Negev. He is working with researchers and students of the Department in developing computational workflows such as data processing, spatial analysis, geostatistics, development of web applications, and web maps, etc., mostly through programming in R, Python, and JavaScript. Michael holds a Ph.D. in Geography and a M.Sc. in Life Sciences from the Ben-Gurion University of the Negev, and a B.Sc. in Plant Sciences in Agriculture from The Hebrew University of Jerusalem. He published two books, "Learning R for Geospatial Analysis" (2014) and "Introduction to Web Mapping" (2020) and authored or co-authored 55 papers in the scientific literature.

  • Introduction to working with spatial data in Python (part 1)
  • Introduction to working with spatial data in Python (part 2)
Nils Ratnaweera

I’m a freelance data scientist (see ratnaweera.xyz/) and researcher at the Zurich University of Applied Sciences (ZHAW) . I enjoy using different programming languages to solve complex, real world problems and answer interesting questions. My tools of choice include R, python, gdal, ogr2ogr, PostgresSQL, PostGIS and more.

  • Hackathons (consultations)
  • Hackathon workshop
  • Announcement of the hackathons winners
Robin Lovelace

Robin Lovelace is Associate Professor of Transport Data Science at the Leeds Institute for Transport Studies (ITS) and Head of Data at the government agency Active Travel England. Robin specializes in geocomputation with a focus on developing geographic methods applied to modeling transport systems, active travel, and decarbonisation. Robin has experience not only researching but deploying transport models in inform sustainable policies and more effective use of transport investment, including as Lead Developer of the Propensity to Cycle Tool (see www.pct.bike), the basis of strategic cycle network plans nationwide. Robin has led numerous data science projects for organizations ranging from the Department for Transport to the World Bank.

Robin is author of popular open source software packages including R packages stplanr, stats19 and abstr. He has authored three reproducible and open source textbooks, Microsimulation with R, Efficient R Programming, and Geocomputation with R.

  • Tidy geographic data with sf, dplyr, ggplot2, geos and friends (part 1)
  • Tidy geographic data with sf, dplyr, ggplot2, geos and friends (part 2)
  • Processing large OpenStreetMap datasets for geocomputational research
Roger Bivand

Roger Bivand is a geographer, emeritus professor at the Department of Economics of the Norwegian School of Economics, Bergen, Norway. His specialties are Geographical Information Analysis, Statistical programming and Spatial econometrics. Roger is author of numerous R packages and was the main author of the Applied Spatial Data Analysis with R book. He is an Ordinary Member of the R Foundation. He has worked with spatial autocorrelation since the 1970’s, and is a Fellow of the Spatial Econometrics Association.

  • Progress in modernizing and replacing infrastructure packages in R-spatial workflows
  • Progress in modernizing and replacing infrastructure packages in R-spatial workflows