Fix QPV validity

GDAL VSICURL tests to remote BDTOPO Geopackage France

This example tests GDAL’s VSICURL virtual file system by streaming a remote GeoPackage of French administrative data, specifically focusing on mairie (town hall) geometries. It demonstrates two ogr2ogr commands that query the BDTOPO dataset using SQL joins to extract mairie footprints as multipolygons and their centroids as points, converting them to GeoJSON with EPSG:4326. The visualization shows how both polygon boundaries and point locations are derived from the same remote source, highlighting the ability to perform spatial SQL operations directly on cloud-hosted vector data without local downloads.

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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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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.

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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 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.

Gist 96068363e74b4c1c148c55aad9ab0cf4

This example demonstrates client-side reprojection of GeoJSON geometries from a source CRS to WGS84 using the Proj4js library. It fetches a French “quartiers prioritaires” dataset encoded in EPSG:2154 and transforms its Point, LineString, Polygon, and Multi* geometries via custom functions that recursively map coordinates through a proj4 transformer. It also tests a second transformation from EPSG:4326 to EPSG:3857 on sample geometries, logging converted coordinates to the console. The code relies on proj4.defs, proj4(...).forward, and the fetch API.

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.

OGR and QGIS MySQL recipes

This example demonstrates how to convert non-spatial MySQL/MariaDB tables with x/y coordinates into viewable vector layers in QGIS. It shows three approaches: using OGR’s SQLite dialect with the `MakePoint` function, using MySQL’s native `ST_PointFromText` function, and creating a geometry column directly in the database. The code uses `ogrinfo`, `ogr2ogr`, and VRT files to bridge GDAL with MySQL, while the final workflow includes loading CSV data through the command line before exporting to the database.