OpenGeoHub Summer School 2023

Introduction to working with spatial data in Python (part 1)
2023-08-28, 11:00–12:30, Room 18 (Sala 18)

Python is an extremely popular general-purpose programming language. It is used in a wide range of settings and for various purposes, including for spatial data processing and analysis.

The aim of this tutorial is to give an introduction to methods of working with spatial data using Python. The tutorial will be split into two parts, introducing two central Python packages:

  • geopandas---For working with vector layers
  • rasterio---For working with rasters

The tutorial will demonstrate typical basic workflows of processing spatial data: data input, processing, geo-computation, and exporting of the results. We will use realistic datasets, such as GTFS public transport data and remote sensing products.

By the end of the tutorial, the participants will be able to:

  • Import spatial data from files
  • Subset and process the data
  • Graphically display the data
  • Perform spatial calculations (such as calculating distances, or applying raster algebra operators)
  • Export the results

To follow along and reproduce the results on your own computer, the prerequisite is to be able to run Python code in a Jupyter Notebook interface, linked to a Python environment with the two above-mentioned packages installed. Instructions will be sent in advance.

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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.

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