Road noise 2017 - future noise levels (day, evening, night)Bruit routier 2017 - future charge sonore (jour, soir, nuit)

Bruit routier 2017 - future charge sonore (jour, soir, nuit)Road noise 2017 - future noise levels (day, evening, night)

APIDiscovered1/7blocked by verifiedQuery nowOpen workbench Subscribe🇫🇷France

This API provides access to a type D noise map produced for the Eurométropole de Strasbourg, showing projected future noise levels linked to new development and infrastructure projects, expressed through the Lden indicator (day, evening, night), for the 2017 reference year. The dataset forms part of the official strategic noise mapping published on the Strasbourg open data portal. More detailed information on noise exposure and related mapping is available on the dedicated pages of the strasbourg.eu website.Carte de bruit de type D représentant la future charge sonore des nouveaux projets d’aménagement et d’infrastructure pour l'indicateur Lden (jour, soir, nuit). Millésime 2017 Une information complète sur le bruit est disponible sur les pages dédiées de strasbourg.eu

environment

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Trust score

How is this computed?

poor

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

Data schema (4 fields)

Filterable via the API (2)

db_lodb_hi

Click a field to see example values.

Field	Type	Description
geo_point_2dGeo Point	geo_point_2d	Geographic coordinates (latitude, longitude) of the noise zone centroid.Geographic coordinates (latitude, longitude) of the noise zone centroid.
geo_shapeShape	geo_shape	Polygon geometry outlining the noise level zone.Polygon geometry outlining the noise level zone.
db_loDb lo	text	Lower bound of the noise level range in decibels (Lden).Lower bound of the noise level range in decibels (Lden).
db_hiDb hi	text	Upper bound of the noise level range in decibels (Lden).Upper bound of the noise level range in decibels (Lden).

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 1db_hi: 99 · db_lo: 75

{
  "db_hi": "99",
  "db_lo": "75",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.62317825752673,
            48.6002828246504
          ],
          [
            7.623113807478969,
            48.60034029308941
          ],
          [
            7.623060163610206,
            48.60028752715241
          ],
          [
            7.622999054259427,
            48.60015482376594
          ],
          [
            7.623090093149654,
            48.60007830853893
          ],
          [
            7.623170175215964,
            48.60014800975915
          ],
          [
            7.62317825752673,
            48.6002828246504
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.6002054576,
    "lon": 7.62309960696
  }
}

Record 2db_hi: 55 · db_lo: 50

{
  "db_hi": "55",
  "db_lo": "50",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.571220608990191,
            48.554232996220996
          ],
          [
            7.571112633436802,
            48.55428921689878
          ],
          [
            7.571011852282354,
            48.55424122272527
          ],
          [
            7.5710992367501,
            48.554139392156095
          ],
          [
            7.571220608990191,
            48.554232996220996
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.5542217981,
    "lon": 7.57111210942
  }
}

Record 3db_hi: 60 · db_lo: 55

{
  "db_hi": "60",
  "db_lo": "55",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.702426431450522,
            48.679402156110626
          ],
          [
            7.702319367765047,
            48.679415005982214
          ],
          [
            7.702310307234611,
            48.67940685222484
          ],
          [
            7.702316865156908,
            48.67938786814046
          ],
          [
            7.702426431450522,
            48.679402156110626
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.6794017883,
    "lon": 7.70235146221
  }
}

Record 4db_hi: 60 · db_lo: 55

{
  "db_hi": "60",
  "db_lo": "55",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.664514405379237,
            48.65282047462998
          ],
          [
            7.664385694592792,
            48.652903977555404
          ],
          [
            7.664246500592895,
            48.65283122678099
          ],
          [
            7.66436876773277,
            48.652718830694226
          ],
          [
            7.664514405379237,
            48.65282047462998
          ]
        ],
        [
          [
            7.664380217653549,
            48.65284407066222
          ],
          [
            7.664410138067248,
            48.65282465939161
          ],
          [
            7.664376282794531,
            48.6528010309919
          ],
          [
            7.66434786029656,
            48.6528271588609
          ],
          [
            7.664380217653549,
            48.65284407066222
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.6528157676,
    "lon": 7.66437895303
  }
}

Record 5db_hi: 55 · db_lo: 50

{
  "db_hi": "55",
  "db_lo": "50",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.698164887393412,
            48.67903385541919
          ],
          [
            7.698009609464625,
            48.679152572457106
          ],
          [
            7.69786276710792,
            48.67904606204264
          ],
          [
            7.697991618135131,
            48.67895729655962
          ],
          [
            7.698164887393412,
            48.67903385541919
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.6790497468,
    "lon": 7.69800986465
  }
}

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

Verification Status

Using the API

Configuration

Base URL: https://data.strasbourg.eu/api/explore/v2.1/catalog/datasets/bruit_d_cos_lda_ems2017

License

Licence Ouverte 2.0 (France / Etalab)Open

✓ Redistributable
✓ Attribution required

Query examples

curl -s 'https://data.strasbourg.eu/api/explore/v2.1/catalog/datasets/bruit_d_cos_lda_ems2017/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

2 000 000 req/day

per ipmeasured

observed 2 days ago

Dataset

Volume & freshness

Records

552

Last upstream update

6 years ago

2020-12-07

License

No license declared upstream.

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Source: opendatasoft

Machine-readable & source

JSON

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