2026-08-12 –, Room 3
Reading and writing geospatial vector data is the bread and butter of any spatial ecosystem. In this short talk we present GeoDataFrames.jl, the default entrypoint for spatial vector data in the JuliaGeo organisation. We discuss recent and planned updates, such as support for native drivers and metadata passthrough, but also spatial indexing and lazy reading of datasets in the cloud.
Every spatial ecosystem needs packages to read and write vector data. In the JuliaGeo ecosystem, we've done so with GDAL, ArchGDAL and GeoDataFrames packages for a long time, slowly introducing more native file formats (ShapeFile, GeoJSON, GeoArrow). In the past (and current) year, GeoDataFrames.jl has seen an uptick in developments, as the community considers the package (should become) an entrypoint for the whole ecosystem.
Recent developments include:
- Native Julia driver support when loaded using extensions
- Metadata passthrough support, keeping metadata intact when possible
- GeometryOps integration, deprecating ArchGDAL operations
- GeometryVector (column) to make some handling of spatial data easier
Future planned developments include:
- Native GeoDataFrame <: AbstractDataFrame type so dispatch becomes easier
- Spatial index support (from GeometryOps) on GeometryVector
- Lazy reading mode
The above two developments (ideally with the new FilePaths design proposals) should enable lazily reading and subsetting of cloud native datasets.
Maarten Pronk is a researcher at Deltares and an external PhD candidate at the Delft University of Technology. He holds a MSc in Geomatics and a BSc in Architecture, both from the Delft University of Technology (NL). His research concerns elevation modelling, especially in lowlands prone to coastal flooding. Currently, he works on applying data from ICESat-2, a LiDAR satellite, to global elevation models.