Kyle Barron
Kyle is a software engineer at Development Seed where he builds open source tools and infrastructure that process and visualize geospatial data. He has expertise in cloud-native geospatial vector data formats, speeding up Python and JavaScript applications from Rust, spatial indexes, and efficient data pipelines. Kyle holds a B.A. in Economics, minoring in Mathematics from the University of California, Los Angeles which he earned in 2017.
Kyle previously worked as a software engineer at Unfolded and then Foursquare, building browser-based geospatial data visualizations on the web for vector and raster data.
Sessions
Lonboard is a new Python library for geospatial vector data visualization that can be 50x faster than existing alternatives like ipyleaflet or pydeck. This talk will explain why this library is so fast, how it integrates into existing workflows, and planned future improvements.
Data protocols enable innovation by providing a stable boundary between data producer and consumer, allowing an ecosystem of libraries to reliably interoperate.
The __geo_interface__ protocol allows transferring GeoJSON-like objects but this can be very slow for large datasets. GeoArrow solves this problem by providing a binary data interchange format for geospatial data.
Existing Python libraries like pyogrio (which binds to GDAL) have achieved massive speedups by adopting GeoArrow. New Python libraries like geoarrow-rust and geoarrow-c store GeoArrow internally, ensuring zero-copy data movement across Python, Rust, and C. Lonboard uses GeoArrow across Python and JavaScript to interactively visualize millions of geometries in Jupyter Notebooks.