2021 Urban Thermal Comfort Index aggregated to a 250m hexagonal gridIndice de confort thermique urbain en 2021 agrégé à la maille hexagonale de 250m

Indice de confort thermique urbain en 2021 agrégé à la maille hexagonale de 250m2021 Urban Thermal Comfort Index aggregated to a 250m hexagonal grid

APIExecutable4/7Query nowOpen workbench Subscribe🇫🇷France

Website Docs

This dataset provides the urban thermal comfort index for 2021, aggregated to a 250-metre hexagonal grid covering the territory of Bordeaux Métropole. It is derived from the 2021 Urban Thermal Comfort Index raster layer, with each hexagon assigned a comfort index value summarizing underlying raster data. Published via the Bordeaux Métropole open data portal, it supports analysis of urban heat and comfort conditions across the metropolitan area, useful for urban planning, climate adaptation studies, and environmental assessment at a sub-communal scale.Dictionnaire Public Ce jeu de données représente l'indice de confort thermique urbain agrégé à la maille hexagonale de 250m sur le territoire de Bordeaux Métropole. Ce jeu a été réalisé à partir du raster Indice de confort thermique urbain 2021 . Pour chaque hexagone est fourni l'indice de confor...

environment

⬇ Export CSV List records Select & filter Run verified request Read the docs

Trust score

How is this computed?

fair

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

Data schema (12 fields)

Filterable via the API (10)

gidictu_minictu_meanictu_medianictu_maxictu_sumictu_countcdatemdategeom_err

Click a field to see example values.

Fill	Field	Type	Description
—	geo_point_2dGeo Point	geo_point_2d	Geographic coordinates of the hexagon's center point.Geographic coordinates of the hexagon's center point.
—	geo_shapeShape	geo_shape	Polygon geometry of the 250m hexagonal cell.Polygon geometry of the 250m hexagonal cell.
—	gid	text	Primary key identifier for the hexagon record.Clé primaire
—	ictu_minIctu min	double	Minimum urban thermal comfort index value in the hexagon.Indice de confort thermique urbain minimal
—	ictu_meanIctu mean	double	Average urban thermal comfort index value in the hexagon.Indice de confort thermique urbain moyen
—	ictu_medianIctu median	double	Median urban thermal comfort index value in the hexagon.Indice de confort thermique urbain médian
—	ictu_maxIctu max	double	Maximum urban thermal comfort index value in the hexagon.Indice de confort thermique urbain maximal
—	ictu_sumIctu sum	double	Sum of all thermal comfort index values in the hexagon.Somme de toutes les valeurs d'ICTU
—	ictu_countIctu count	text	Number of thermal comfort index values in the hexagon.Nombre de valeurs d'ICTU
—	cdate	datetime	Date and time the record was created.Date de création
100%	mdate	datetime	Date and time the record was last modified.Date de modification
0%	geom_errGeom err	text	Error code indicating a geometric data issue, if any.Code d'erreur géométrique : Liste des valeurs possibles : 9999 : Polygone compose et / ou à sections multiples 9998 : Linéaire compose et / ou à sections multiples 9996 : La géométrie contient des informations LRS 9995 : Nombre de dimensions différent de 2 ou 3 9994 : Présence d'un arc de cercle 9000 : Erreur autre 13343 : Polygone de moins de 4 points 13349 : Polygone papillon 13350 : Deux éléments d'un polygone archipel se touchent 13351 : Deux éléments d'un polygone archipel se touchent 13356 : Point double 13366 : Combinaison invalide d'intérieur / extérieur d'un polygone 13367 : Orientation invalide d'intérieur / extérieur d'un polygone

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.

Where=

Sort by

Sample data (5 records)

Record 1gid: 40164 · cdate: 2025-09-01T17:03:50+00:00

{
  "gid": "40164",
  "cdate": "2025-09-01T17:03:50+00:00",
  "mdate": "2025-09-01T17:03:50+00:00",
  "geom_err": null,
  "ictu_max": 2.49,
  "ictu_min": 0.4,
  "ictu_sum": 11146.01,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            -0.5628225,
            44.847094
          ],
          [
            -0.5618409,
            44.8459988
          ],
          [
            -0.5600168,
            44.8460558
          ],
          [
            -0.5591742,
            44.8472082
          ],
          [
            -0.5601557,
            44.8483035
          ],
          [
            -0.5619799,
            44.8482464
          ],
          [
            -0.5628225,
            44.847094
          ]
        ]
      ]
    },
    "properties": {}
  },
  "ictu_mean": 1.49,
  "ictu_count": "7488",
  "ictu_median": 1.43,
  "geo_point_2d": {
    "lat": 44.84715112951739,
    "lon": -0.5609983269239585
  }
}

Record 2gid: 39903 · cdate: 2025-09-01T17:03:47+00:00

{
  "gid": "39903",
  "cdate": "2025-09-01T17:03:47+00:00",
  "mdate": "2025-09-01T17:03:47+00:00",
  "geom_err": null,
  "ictu_max": 2.34,
  "ictu_min": 1.4,
  "ictu_sum": 23763.22,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            -0.8355371,
            44.8663843
          ],
          [
            -0.83455,
            44.8652914
          ],
          [
            -0.8327255,
            44.8653528
          ],
          [
            -0.8318881,
            44.8665072
          ],
          [
            -0.8328751,
            44.8676001
          ],
          [
            -0.8346997,
            44.8675387
          ],
          [
            -0.8355371,
            44.8663843
          ]
        ]
      ]
    },
    "properties": {}
  },
  "ictu_mean": 1.76,
  "ictu_count": "13534",
  "ictu_median": 1.78,
  "geo_point_2d": {
    "lat": 44.866445756439056,
    "lon": -0.8337125897734844
  }
}

Record 3gid: 41652 · cdate: 2025-09-01T17:04:16+00:00

{
  "gid": "41652",
  "cdate": "2025-09-01T17:04:16+00:00",
  "mdate": "2025-09-01T17:04:16+00:00",
  "geom_err": null,
  "ictu_max": 2.9,
  "ictu_min": 0.86,
  "ictu_sum": 25964.14,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            -0.5599893,
            44.8899705
          ],
          [
            -0.559007,
            44.8888752
          ],
          [
            -0.5571816,
            44.8889323
          ],
          [
            -0.5563383,
            44.8900846
          ],
          [
            -0.5573205,
            44.8911799
          ],
          [
            -0.559146,
            44.8911229
          ],
          [
            -0.5599893,
            44.8899705
          ]
        ]
      ]
    },
    "properties": {}
  },
  "ictu_mean": 2.05,
  "ictu_count": "12636",
  "ictu_median": 2.03,
  "geo_point_2d": {
    "lat": 44.89002757782381,
    "lon": -0.5581638038815145
  }
}

Record 4gid: 41527 · cdate: 2025-09-01T17:04:13+00:00

{
  "gid": "41527",
  "cdate": "2025-09-01T17:04:13+00:00",
  "mdate": "2025-09-01T17:04:13+00:00",
  "geom_err": null,
  "ictu_max": 2.9,
  "ictu_min": 1.21,
  "ictu_sum": 29619.29,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            -0.6688521,
            44.9191718
          ],
          [
            -0.6678673,
            44.9180774
          ],
          [
            -0.666041,
            44.9181362
          ],
          [
            -0.6651994,
            44.9192893
          ],
          [
            -0.6661842,
            44.9203837
          ],
          [
            -0.6680105,
            44.9203249
          ],
          [
            -0.6688521,
            44.9191718
          ]
        ]
      ]
    },
    "properties": {}
  },
  "ictu_mean": 2.38,
  "ictu_count": "12460",
  "ictu_median": 2.52,
  "geo_point_2d": {
    "lat": 44.919230549999995,
    "lon": -0.667025749999999
  }
}

Record 5gid: 40367 · cdate: 2025-09-01T17:03:54+00:00

{
  "gid": "40367",
  "cdate": "2025-09-01T17:03:54+00:00",
  "mdate": "2025-09-01T17:03:54+00:00",
  "geom_err": null,
  "ictu_max": 1.07,
  "ictu_min": 0.95,
  "ictu_sum": 89.46,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            -0.5448054,
            44.9107117
          ],
          [
            -0.5438231,
            44.9096163
          ],
          [
            -0.5419969,
            44.9096731
          ],
          [
            -0.541153,
            44.9108253
          ],
          [
            -0.5421353,
            44.9119208
          ],
          [
            -0.5439615,
            44.911864
          ],
          [
            -0.5448054,
            44.9107117
          ]
        ]
      ]
    },
    "properties": {}
  },
  "ictu_mean": 1.01,
  "ictu_count": "89",
  "ictu_median": 1,
  "geo_point_2d": {
    "lat": 44.91076854440196,
    "lon": -0.5429792013656969
  }
}

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/ri_ictu_s

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/ri_ictu_s/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

11k

11056

Last upstream update

29 days ago

2026-09-25

License

No license declared upstream.

○ Documentation○ Data dictionary○ Versioning

Source: opendatasoft

Machine-readable & source

JSON

Embed this badge in a README or wiki — it always shows the latest verification state and quality tier.