Noise Map 2017 - Areas Exposed to Rail Noise (Night)Bruit 2017 - Zones exposées au bruit ferroviaire (nuit)

Name: Noise Map 2017 - Areas Exposed to Rail Noise (Night)
Creator: opendatasoft

Bruit 2017 - Zones exposées au bruit ferroviaire (nuit)Noise Map 2017 - Areas Exposed to Rail Noise (Night)

APIExecutable4/7Query nowOpen workbench Subscribe🇫🇷France

This API provides access to a noise map showing areas exposed to railway noise for the Ln (night) indicator, dated 2017. It is published by the Eurométropole de Strasbourg and covers the Strasbourg metropolitan area in France. The dataset forms part of a broader set of noise-mapping data available on the strasbourg.eu open data portal, offering more complete information on noise exposure across the territory. It can be used for environmental assessment, urban planning, and noise pollution monitoring purposes.Carte de bruit des zones exposées au bruit ferroviaire pour l'indicateur Ln (nuit). Millésime 2017 Une information complète sur le bruit est disponible sur les pages dédiées de strasbourg.eu

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Trust score

How is this computed?

fair

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	—
geo_shapeShape	geo_shape	—
db_loDb lo	text	—
db_hiDb hi	text	—

Schema captured from opendatasoft 7 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: 65 · db_lo: 60

{
  "db_hi": "65",
  "db_lo": "60",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.676173024607758,
            48.55892374861657
          ],
          [
            7.67617032783884,
            48.558943780693966
          ],
          [
            7.676033480097373,
            48.55893153285717
          ],
          [
            7.676026961913265,
            48.558929636496025
          ],
          [
            7.676033207722143,
            48.558928555485544
          ],
          [
            7.676145967154512,
            48.55883474313305
          ],
          [
            7.67615746564638,
            48.55880318605146
          ],
          [
            7.676275490316329,
            48.55882952183882
          ],
          [
            7.676173024607758,
            48.55892374861657
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.5588778212,
    "lon": 7.6761571778
  }
}

Record 2db_hi: 65 · db_lo: 60

{
  "db_hi": "65",
  "db_lo": "60",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.657733513993423,
            48.55416980160133
          ],
          [
            7.657686192521416,
            48.55419702687422
          ],
          [
            7.657652323454325,
            48.55417306183674
          ],
          [
            7.657682529661316,
            48.554156825719
          ],
          [
            7.657733513993423,
            48.55416980160133
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.554174974,
    "lon": 7.65769022205
  }
}

Record 3db_hi: 65 · db_lo: 60

{
  "db_hi": "65",
  "db_lo": "60",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.655472958661791,
            48.55371998432045
          ],
          [
            7.655472045395359,
            48.55372766000965
          ],
          [
            7.655336357740543,
            48.55372791907927
          ],
          [
            7.655328724672477,
            48.55372577328289
          ],
          [
            7.655336039183079,
            48.553724421001846
          ],
          [
            7.655452008401137,
            48.553630730293
          ],
          [
            7.65546130800581,
            48.553609755983665
          ],
          [
            7.655544838637395,
            48.553627004381724
          ],
          [
            7.655472958661791,
            48.55371998432045
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.5536771022,
    "lon": 7.65544909065
  }
}

Record 4db_hi: 65 · db_lo: 60

{
  "db_hi": "65",
  "db_lo": "60",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.654804494338232,
            48.5535666225221
          ],
          [
            7.654780327541079,
            48.55358311348905
          ],
          [
            7.654728336498567,
            48.55356967877814
          ],
          [
            7.654776461484009,
            48.55354065510342
          ],
          [
            7.654804494338232,
            48.5535666225221
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.5535641403,
    "lon": 7.65477023349
  }
}

Record 5db_hi: 65 · db_lo: 60

{
  "db_hi": "65",
  "db_lo": "60",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.6488434383150254,
            48.55209389624113
          ],
          [
            7.648810791079939,
            48.552109744825
          ],
          [
            7.648761521647606,
            48.55209717947606
          ],
          [
            7.648806651894009,
            48.55206422699249
          ],
          [
            7.6488434383150254,
            48.55209389624113
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.55208993,
    "lon": 7.64880430975
  }
}

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_a_fer_lna_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_a_fer_lna_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 7 days ago

Dataset

Volume & freshness

Records

4.5k

4500

Last upstream update

6 years ago

2020-12-07

License

No license declared upstream.

○ Documentation○ Data dictionary○ Versioning

Source: opendatasoft

Machine-readable & source

JSON

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