GDAL VSICURL tests to remote BDTOPO Geopackage France

Query remote Geoparquet in browser

This example demonstrates querying a remote GeoParquet file directly from a web browser using DuckDB-Wasm. The interactive map displays French priority neighborhoods (QPVs) and identifies which one contains a specific geographic point (2.389798, 48.909514). It uses DuckDB-Wasm’s SQL engine with the spatial extension to run an `ST_contains` query, filtering results by geometric intersection. The workflow converts the matched polygons to GeoJSON via the GDAL driver and exports them as a downloadable file. The dataset was prepared from a government GeoJSON source using DuckDB and gpio utilities.

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Gist 349fc7fda8932252cbcb4ee8a0b605c8

This example tracks the availability and licensing of the French IGN’s BD TOPO® departmental datasets by organizing URLs for both December 2021 and March 2021 releases. It shows a structured index of geographic data files, with each entry linking to a specific departmental Shapefile resource. The visualization uses a data-driven list format, likely rendered with JavaScript’s `fetch` to parse the provided CSV or JSON and display the sorted URLs. It highlights the variation in resource IDs across departments and time periods, emphasizing the dataset’s scope without mapping or spatial rendering.

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Export DVF geolocalisées en Geoparquet

This example converts French land-registry transaction data (DVF) from compressed CSV files into a single spatially-indexed GeoParquet file. It downloads yearly datasets from data.gouv.fr, loads them into a DuckDB database, and creates a point geometry for each transaction before exporting with a Hilbert-curve spatial ordering. The script leverages DuckDB’s spatial extension, the `ST_Point` and `ST_Hilbert` functions, and parquet compression via zstd.

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Generation GeoJSON des mairies avec code INSEE

This example generates a GeoJSON file of French town halls (mairies) with their INSEE commune codes, distinguishing principal towns from associated communes. It uses `ogr2ogr` with an SQLite dialect to join commune boundaries with their chief-town points from the IGN ADMIN-EXPRESS dataset, applying `PointOnSurface` as a fallback when no official point exists. The resulting output is written with RFC 7946 compliance for modern web mapping. The script downloads a 7z archive and extracts the necessary shapefiles before performing the spatial join.

Gist 8dafcac4cab52f5242b00c077430c08d

This example demonstrates how to select cadastral parcels from the IGN Cadastre API based on a drawn polygon’s extent. It shows the process of converting a GeoJSON polygon into an encoded URL parameter, then sending a GET request via Bash with `jq` or Python with `urllib.parse` and `urllib.request`. The API returns parcel geometries, which are saved as a GeoJSON file. The code also warns against using overly complex or overly large geometries due to URL length limits and server load.

Gist c8b3e33ae90180e985646e1ef4876dfe

This example demonstrates how to convert tabular JSON data containing longitude and latitude fields into a GeoJSON FeatureCollection using the command-line tool jq, making it ready for map-based visualization. The dataset covers digital mediation locations in the Auvergne-Rhône-Alpes region of France, sourced from data.gouv.fr. The transformation maps each original record into a GeoJSON Feature, preserving properties like name, address, services, and accessibility conditions, while constructing Point geometry from the coordinate pair. The code includes a preview image showing the resulting spatial distribution of these locations, though the visualization itself uses no specific JavaScript mapping library or framework beyond the jq conversion process.

Load GTFS as GPKG with GDAL 3.7

This example demonstrates converting an IDFM GTFS transit feed into a GeoPackage database using GDAL’s new GTFS driver. The Bash script first checks that GDAL 3.7 is installed, then uses `ogrinfo` with `-json` to list all available layers. For each layer, it runs `ogr2ogr` with the GeoPackage format, appending layers incrementally with the `-update` flag. The source data is loaded directly from a URL via `/vsicurl/`, and the script allows customizing input and output names through environment variables.

VRT to merge vector data

This example demonstrates how to merge multiple vector datasets into a single unified dataset using the Virtual Dataset (VRT) format, specifically for French IRIS geographic zones. It shows the workflow of combining shapefiles from different territories and projections into one WGS 84 layer without creating an intermediate file, then converting the result to GeoPackage and PostGIS formats. The code uses the `ogrmerge.py` GDAL utility to create the VRT, `ogr2ogr` for format conversions, and psql commands for database setup.