Urban Furniture: Free-Standing Billboard Panels of the City of BordeauxMobiliers urbains : Panneaux d'affichage libre de la ville de Bordeaux

Mobiliers urbains : Panneaux d'affichage libre de la ville de BordeauxUrban Furniture: Free-Standing Billboard Panels of the City of Bordeaux

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This API provides the locations of free advertising billboard panels installed on public land within the city of Bordeaux. It is published as part of the Bordeaux Métropole open data platform and offers a geolocated dataset of these urban furniture items. The data can be used for mapping public advertising infrastructure, urban planning analysis, or integration into other municipal services related to public space management within the Bordeaux metropolitan area.Emplacement des panneaux d'affichage libre sur le domaine public.

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Trust score

How is this computed?

poor

Weighted across five axes. Tap a ring for what it measures.

Data schema (8 fields)

Filterable via the API (6)

gidnombrecdatemdategml_idgeom_o

Click a field to see example values.

Field	Type	Description
geo_point_2dGeo Point	geo_point_2d	Geographic coordinates (latitude, longitude) of the billboard.Geographic coordinates (latitude, longitude) of the billboard.
geo_shapeShape	geo_shape	Geometric shape (GeoJSON) representing the billboard's location.Geometric shape (GeoJSON) representing the billboard's location.
gid	int	Internal numeric identifier of the record.Internal numeric identifier of the record.
nombre	int	Number of billboard panels at the location.Number of billboard panels at the location.
cdate	datetime	Date and time the record was created.Date and time the record was created.
mdate	datetime	Date and time the record was last modified.Date and time the record was last modified.
gml_idGml id	text	Unique GML identifier for the geographic feature.Unique GML identifier for the geographic feature.
geom_oGeom o	int	Original geometry order or index value.Original geometry order or index value.

Schema captured from opendatasoft 2 days ago.

Query the data

Pick columns and a sort, then fetch a live preview straight from the source. Choose an API-filterable column (marked ▾) under “Where” to pick from its list of values.

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Sample data (5 records)

Record 1gid: 5762 · cdate: 2023-03-03T13:05:42+00:00

{
  "gid": 5762,
  "cdate": "2023-03-03T13:05:42+00:00",
  "mdate": "2023-03-03T13:06:55+00:00",
  "geom_o": 0,
  "gml_id": "_4bbadc8c-2972-11eb-a9a2-fb0a0f0c06c1.5762",
  "nombre": 2,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Point",
      "coordinates": [
        -0.623472222222229,
        44.857944444444364
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 44.857944444444364,
    "lon": -0.623472222222229
  }
}

Record 2gid: 5759 · cdate: 2023-03-03T13:05:41+00:00

{
  "gid": 5759,
  "cdate": "2023-03-03T13:05:41+00:00",
  "mdate": "2023-03-03T13:06:53+00:00",
  "geom_o": 0,
  "gml_id": "_4bbadc8c-2972-11eb-a9a2-fb0a0f0c06c1.5759",
  "nombre": 2,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Point",
      "coordinates": [
        -0.5575,
        44.84366666666656
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 44.84366666666656,
    "lon": -0.5575000000000345
  }
}

Record 3gid: 5698 · cdate: 2023-03-03T13:05:37+00:00

{
  "gid": 5698,
  "cdate": "2023-03-03T13:05:37+00:00",
  "mdate": "2023-03-03T13:06:28+00:00",
  "geom_o": 0,
  "gml_id": "_4bbadc8c-2972-11eb-a9a2-fb0a0f0c06c1.5698",
  "nombre": 2,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Point",
      "coordinates": [
        -0.549472222222274,
        44.87366666666655
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 44.87366666666655,
    "lon": -0.5494722222222743
  }
}

Record 4gid: 5725 · cdate: 2023-03-03T13:05:39+00:00

{
  "gid": 5725,
  "cdate": "2023-03-03T13:05:39+00:00",
  "mdate": "2023-03-03T13:06:39+00:00",
  "geom_o": 0,
  "gml_id": "_4bbadc8c-2972-11eb-a9a2-fb0a0f0c06c1.5725",
  "nombre": 2,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Point",
      "coordinates": [
        -0.60725,
        44.83680555555544
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 44.83680555555544,
    "lon": -0.6072499999999342
  }
}

Record 5gid: 5699 · cdate: 2023-03-03T13:05:37+00:00

{
  "gid": 5699,
  "cdate": "2023-03-03T13:05:37+00:00",
  "mdate": "2023-03-03T13:06:28+00:00",
  "geom_o": 0,
  "gml_id": "_4bbadc8c-2972-11eb-a9a2-fb0a0f0c06c1.5699",
  "nombre": 2,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Point",
      "coordinates": [
        -0.549527777777829,
        44.8645
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 44.86449999999994,
    "lon": -0.5495277777778288
  }
}

Live sample captured at profiling time — values may have changed upstream.

Verification Status

Using the API

Configuration

Base URL: https://opendata.bordeaux-metropole.fr/api/explore/v2.1/catalog/datasets/bor_sigpanneaux

License

Licence Ouverte 2.0 (France / Etalab)Open

✓ Redistributable
✓ Attribution required

Query examples

curl -s 'https://opendata.bordeaux-metropole.fr/api/explore/v2.1/catalog/datasets/bor_sigpanneaux/records?limit=20' -H 'Accept: application/json'

First 20 records of the dataset as JSON.

Uses the Opendatasoft Explore v2.1 syntax — supports select, where, group_by and order_by.

Full API documentation ↗

Rate limits

50 000 req/day

per ipmeasured

observed 2 days ago

Dataset

Volume & freshness

Records

Update cadence

Quarterly

declared upstream

Last upstream update

3 days ago

2026-10-21

License

No license declared upstream.

○ Documentation○ Data dictionary○ Versioning

Source: opendatasoft

Machine-readable & source

JSON

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