NFDI4Earth - Geospatial Intelligence for Sustainable Futures: Smart Data and AI Applications

This course offers a comprehensive introduction to artificial intelligence (AI) and geospatial data analysis, focusing on urbanisation and sustainable development. The first part explores the impacts of urbanisation on socio-ecological systems, with an emphasis on Sustainable Development Goal 11. Learners will gain skills in accessing and processing geospatial data from sources like open geodata, volunteered geographic information (VGI), social media geographic information (SMGI), and earth observation (EO) data using Python, while studying urban transformations through regional case studies.
The second part introduces machine learning and deep learning, focusing on AI techniques such as Random Forest, Support Vector Machines, and neural networks for pattern recognition, prediction, and geosimulation. Learners will gain practical experience in applying these AI methods to geographic problems using GIS environments and Python scripts. By the end of the course, participants will be equipped to apply machine learning and AI tools to real-world geospatial data, answering research questions related to urbanisation and sustainability.
Together, these modules provide hands-on experience in analysing geospatial data and applying AI in the context of urban studies and sustainable development.
 

The learning module was created as part of the NFDI4Earth project
 „NFDI4Earth will provide simple, efficient, open, and – whenever possible – unrestricted access to all relevant Earth system data, scientific data management and data analysis services. Major implementation guidelines are the FAIR principles which do impact the whole research data life cycle.“ – nfdi4earth.de/about-us