In this lesson you will learn how to work with geospatial datasets and how to process these with Python. Python is one of the most popular programming languages for data science and analytics, with a large and steadily growing community in the field of Earth and Space Sciences. The lesson is meant for participants with a basic knowledge of Python and it allows them to familiarize with the world of geospatial raster and vector data.
You will be introduced to a set of tools from the Python ecosystem and learn how these can be used to carry out geospatial data analysis tasks. In particular, you will work with satellite images and open topographical geo-datasets, and learn how these spatial datasets can be accessed, explored, manipulated and visualized using Python.
Difficulty rating: ★★★☆ Intermediate
Who is it for?
- Both research staff and research students
- Users who are already familiar with the basics of Python
Summary of the topics covered
- Understanding the differences between raster and vector geospatial data and when you might be able to use one or the other
- Downloading, analysing and visualising raster satellite data from the Copernicus Sentinel-2 mission (and other SpatioTemporal Asset Catalog (STAC) based services)
- Exploring vector data from OpenStreetMap, and combine that with satellite data.
Prerequisites
Either attendance at Software Carpentry - Python or previous experience in using Python is required.
Frequency
2 times a year
Duration
7 hours
Next course
4th November, full day. Book here
Can't attend?
We don’t have online materials for this session, but the course will run again — so you’ll be very welcome to join next time.