PhD Courses in Denmark

Description: The PhD course Python for Geospatial Analysis will provide an introduction to Python with a focus on mapping, exploring, processing, and analysing geospatial information using Python. Participants will learn how tasks traditionally conducted in a desktop GIS system can be easily transferred to Python code and therefore made faster, more flexible, and completely reproducible, which is an aspect of increasing importance in many research fields. At the end of this course, participants will have a solid understanding of the capabilities of core Python modules for geospatial information such as fiona, geopandas, pysal, or rasterio and be able to apply them in their own research. This course will focus on geospatial analysis in “pure” Python, i.e., automation of tasks in ArcGIS or QGIS with Python is out of scope for this course. However, participants looking to do this should be sufficiently proficient in Python after this course to accomplish these tasks on their own. 

Day 1: General introduction to Python, mapping and explorative analysis of geographic information 

Day 2: The Python stack for geospatial analysis 

Day 3: Using geospatial web services from Python

Prerequisites: The course will introduce Python from scratch (i.e., no previous experience in Python is required), however participants should have a basic understanding of programming principles, e.g. know what a variable, a function, or a loop is. Likewise, we do not expect participants to be GIS experts, but again, a basic understanding of geographic information concepts such as layers or vector/raster formats. Ideally, participants in this course would already be using GIS in some way for their research and be looking for ways to do this more efficiently. 

Learning objectives: The participants will be able to use python for - automating generic tasks such as e.g., downloading online data and basic data science tasks, - interacting with cloud services and processing data in the cloud systems, - visualising, processing, and analysing geospatial data using geospatial methods, - solving their own self-defined tasks related to their PhD.

Organizer: Jamal Jokar Arsanjani

Lecturers: Jamal Jokar Arsanjani, Carsten Kessler, Ida Maria Bonnevie, Irma Kveladze

ECTS: 3

Time: 14 - 16 May 2025

Place: Aalborg University

Zip code: 2450

City: Copenhagen

Maximal number of participants: 20

Deadline: 23 April 2025