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The official Jupyter Conference
August 22-23, 2017: Training
August 23-25, 2017: Tutorials & Conference
New York, NY

GeoNotebook: An extension to the Jupyter Notebook for exploratory geospatial analysis

2:40pm–3:20pm Thursday, August 24, 2017
Extensions and customization
Location: Beekman/Sutton North Level: Intermediate
Average rating: ****.
(4.00, 1 rating)

Who is this presentation for?

  • Data scientists, climate scientists, and geospatial experts

Prerequisite knowledge

  • Familiarity with geospatial data concepts (e.g., the difference between vector data, such as geoJSON, and raster data, such as geoTIFF) (useful but not required)

What you'll learn

  • Explore the architecture, capabilities, and use cases of GeoNotebook, an exciting new extension to Jupyter Notebook that provides interactive visualization and analysis of geospatial data


Chris Kotfila offers an overview of GeoNotebook, an exciting new extension to Jupyter Notebook that provides interactive visualization and analysis of geospatial data. Unlike other geospatial extensions to the Jupyter Notebook, GeoNotebook includes a fully integrated tile server providing easy visualization of on-disk vector and raster data formats, giving users the ability to zoom and pan through their data, interactively subset that data via points, rectangles and polygons, and interact with those subsets (as NumPy arrays) from inside a notebook.

GeoNotebook is designed to appeal to geospatial experts who are interested in using state-of-the-art data science tools like the Jupyter Notebook to explore their data and share their findings, data scientists who are already using the Python data analytics stack but find current geospatial libraries to be confusing or burdensome, and technical managers of large quantities of geospatial data who are looking to maximize usage by providing secure analysis environments that are closer their data. GeoNotebook achieves this through a server extension that integrates a full open source tiling server into the Jupyter Notebook and by leveraging Jupyter’s comm infrastructure to provide remote synchronization between the Python kernel and a single, large interactive client-side map.

Chris also briefly explores the plugin’s architecture and some NASA climate use cases for which the plugin is being developed and leads a live demonstration of the GeoNotebook plugin’s capabilities.

Photo of Christopher Kotfila

Christopher Kotfila


Chris Kotfila is an R&D engineer at Kitware. Chris’s research interests are in natural language processing, machine learning, knowledge organization and geographic information science. He holds dual degrees in computer science and philosophy from Rensselaer Polytechnic Institute and a master’s degree in library science, where he focused on issues of open access, scholarly communication and reproducible research. During his time at RPI, he worked regularly as a research programmer in the area of computational cognitive engineering. Chris also served overseas with the US Peace Corps. He is an avid open source enthusiast and a hopeless Emacs user.