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Geoscripting

GRS33806

About this course

Solve geographical and any spatial applied problems through scripting.
Professionals in private companies and research institutes are increasingly using scripting languages for applied spatial analysis. Many students still have a “scripting” barrier to overcome. In Geoscripting you will be introduced to programming in a gentle and applied fashion aimed to make scripting more accessible.
Geoscripting will help advanced programmers to delve into geospatial problems, but the focus is on scripting, so the course is also suitable for early stage programmers as well. During Geoscripting you will learn how to use free and open-source software to deal with spatial vector and raster data, such as field survey point data and satellite imagery used in remote sensing studies. You will replace the traditional memorising cookbook approach to scripting with an explorative approach. You will learn how to search for solutions both online, and among your peers, and you are encouraged to have a try-out mindset during the project weeks. Good scripting habits are paramount to great collaborative programming projects, so you will learn about version control and other key tools for a successful project.

Learning outcomes

After successful completion of this course students are expected to be able to:

  • Demonstrate scripting skills by writing clear, documented and reproducible scripts to read, write and visualise spatial data
  • Apply version control supporting effective collaboration in a team
  • Use documentation, search tools and contribute to discussion platforms with reproducible examples as an aid to solve scripting challenges effectively
  • Use and create open-source software with an appropriate software license
  • Combine functions from novel libraries to efficiently process spatial data
  • Create an integrated software project that solves a spatial challenge

Prior knowledge

Assumed Knowledge:
Students should have basic programming knowledge (equivalent to INF22306 Programming in Python or MAT50303 R for Statistics), ideally in both R and Python, and also have a good understanding of spatial data (vector, raster) via GRS10306 (Introduction Geo-Information Science) or equivalent.

Resources

Additional information

  • Credits
    ECTS 6
  • Level
    bachelor
  • Selection course
    No
If anything remains unclear, please check the FAQ of Wageningen University.
There are currently no offerings available for students of TU Eindhoven