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Geospatial Data Science is the discipline of distilling insights from any source of data that comes with a spatial component. It is estimated that 60-80% of all information is geospatially referenced, but only few companies are aware of – let alone exploit – the full potential of geospatial data. Understanding why things happen where allows companies to predict and influence where things will happen next and thereby boost the effectiveness of marketing and advertising campaigns, optimize supply chains and logistics, improve customer experience and make more informed decisions about where to invest in their own innovations, to name but a few.

In this workshop, we will introduce participants to the basic concepts of geospatial data science, including an overview of geographical coordinate systems, data types and commonly-used tools and frameworks for storing, manipulating and visualizing geodata. Furthermore, we will discuss existing and brainstorm potential future use cases across various sectors.

In the hands-on part that follows, we guide participants through a data pipeline in which they use open-source datasets to investigate and predict natural hazards relating to climate-change in Switzerland. Participants will use Python to analyze various data types at different geospatial resolutions as they occur in the respective datasets. By the end of the workshop, participants will know how to explore, visualize, and manipulate location-based data, how to use it in predictive modeling, and the state-of-the-art tools that allow them to do so in Python.


09:00 – 09:10 Theory What is geospatial data science? An overview
09:10 – 09:20 Geographical coordinate systems
09:20 – 09:30 Data types
09:30 – 09:35 Common tools and frameworks
09:35 – 09:45 Use cases in the industry
09:45 – 10:00 Hands-On Introduction to geopandas and rasterio
10:00 – 10:30 Data exploration and visualization
10:30 – 10:45 Coffee Break
10:45 – 11:00 Spatial joins
11:00 – 11:45 ML use case
11:45 – 12:00 Participant use cases + Q&A