2026-08-30 –, 609
Learn how to build modern geospatial workflows using Python. This hands-on workshop covers spatial analysis with GeoPandas, network analysis with OSMnx, and interactive web mapping with Pydeck and Streamlit using real-world geospatial datasets
This hands-on workshop introduces practical geospatial data science workflows using open-source Python tools. Participants will learn how to process, analyze, and visualize spatial datasets using libraries such as GeoPandas, OSMnx, NetworkX, and Pydeck.
The workshop focuses on building an end-to-end geospatial workflow—from spatial data processing and network analysis to interactive web-based mapping. Participants will develop a lightweight geospatial application that integrates spatial analysis results with interactive visualization using Streamlit.
Rather than relying solely on traditional desktop GIS software, this workshop demonstrates how modern Python-based open-source tools can support scalable and reproducible geospatial analysis workflows for urban analytics, transportation studies, and spatial data science projects.
Participants should bring a laptop with Python installed.
Prior installation of GeoPandas, OSMnx, NetworkX, Pydeck, and Streamlit is recommended.
Basic familiarity with Python and GIS concepts will help participants follow the exercises more easily.
Participants should have basic Python programming knowledge, including working with Jupyter notebooks and installing Python packages.
Familiarity with basic GIS concepts such as coordinates, spatial data formats, and maps will be helpful but is not strictly required.
Yeonjun Kim is a geospatial data scientist and GIS educator specializing in spatial data science using open-source tools. He works with Python-based geospatial technologies such as GeoPandas, OSMnx, and Pydeck to develop spatial analysis workflows and interactive mapping applications. He has experience teaching spatial data analysis, Python programming, and GIS to researchers, engineers, and data professionals.