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Industrial noise 2017 - Threshold exceedance (day, evening, night)Bruit industriel 2017 - Dépassement des seuils (jour, soir, nuit)

Bruit industriel 2017 - Dépassement des seuils (jour, soir, nuit)Industrial noise 2017 - Threshold exceedance (day, evening, night)

APIDiscovered1/7blocked by verifiedQuery nowOpen workbenchSubscribe🇫🇷France

This API provides access to a Type C noise map showing areas where regulatory limit values for industrial noise, measured by the Lden indicator (day, evening, night), exceed 71 dB(A). The data corresponds to the 2017 reference year and covers the Strasbourg area in France. It is published as part of the Eurométropole de Strasbourg open data portal. Further comprehensive information on noise is available on dedicated pages of the strasbourg.eu website.Carte de type C indiquant les zones où les valeurs limites réglementaires pour le bruit industriel pour l'indicateur Lden (jour, soir, nuit) dépassent 71 dB(A). Millésime 2017 Une information complète sur le bruit est disponible sur les pages dédiées de strasbourg.eu

environment
35
poor

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

Data schema (5 fields)

Filterable via the API (3)
db_lodb_hifme_feature_type

Click a field to see example values.

FieldTypeDescription
geo_point_2dGeo Pointgeo_point_2dGeographic coordinates of the zone's center point.Geographic coordinates of the zone's center point.
geo_shapeShapegeo_shapePolygon geometry outlining the noise exceedance zone.Polygon geometry outlining the noise exceedance zone.
db_loFilterable via the APIDb lotextLower bound of the Lden noise level range in dB(A).Lower bound of the Lden noise level range in dB(A).
db_hiFilterable via the APIDb hitextUpper bound of the Lden noise level range in dB(A).Upper bound of the Lden noise level range in dB(A).
fme_feature_typeFilterable via the APIFme feature typetextInternal feature type code identifying the source dataset layer.Internal feature type code identifying the source dataset layer.

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.

=

Sample data (5 records)

Record 1db_hi: 1000000 · db_lo: 71
{
  "db_hi": "1000000",
  "db_lo": "71",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.795875896341832,
            48.54580052285862
          ],
          [
            7.795742406130024,
            48.545824137595936
          ],
          [
            7.795708910108113,
            48.54575345826966
          ],
          [
            7.795593163917534,
            48.54567982601893
          ],
          [
            7.795571949201515,
            48.545669017041156
          ],
          [
            7.795450830469922,
            48.54560916024098
          ],
          [
            7.795317078087775,
            48.545589451542995
          ],
          [
            7.795322993251383,
            48.54549910176111
          ],
          [
            7.795389907618666,
            48.54540622950869
          ],
          [
            7.795431284860134,
            48.54540078216849
          ],
          [
            7.795564122285731,
            48.54537021875468
          ],
          [
            7.795671940938476,
            48.54530446111012
          ],
          [
            7.795690671569457,
            48.5452726215281
          ],
          [
            7.795827403348567,
            48.5452835780422
          ],
          [
            7.795877946796582,
            48.54529594150468
          ],
          [
            7.795967341932808,
            48.545328718284004
          ],
          [
            7.796047701162116,
            48.54537902608141
          ],
          [
            7.796112094859201,
            48.54542517493408
          ],
          [
            7.796157437058628,
            48.54546459276811
          ],
          [
            7.79620266039598,
            48.54555282759692
          ],
          [
            7.796131336690028,
            48.54563028510181
          ],
          [
            7.796119445244751,
            48.54564637454858
          ],
          [
            7.796036912735715,
            48.54573989319229
          ],
          [
            7.796007298763888,
            48.54575465386045
          ],
          [
            7.795875896341832,
            48.54580052285862
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.5455348426,
    "lon": 7.79578032472
  },
  "fme_feature_type": "C__industrie_LDC__EMS2017"
}
Record 2db_hi: 1000000 · db_lo: 71
{
  "db_hi": "1000000",
  "db_lo": "71",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.788035807472617,
            48.53841162166335
          ],
          [
            7.787993660702045,
            48.538434302979915
          ],
          [
            7.787917984650731,
            48.53841648708173
          ],
          [
            7.787890544380207,
            48.53832751533583
          ],
          [
            7.78797713311145,
            48.53825780017625
          ],
          [
            7.78808983983114,
            48.53831928551939
          ],
          [
            7.788035807472617,
            48.53841162166335
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.5383490965,
    "lon": 7.78798453689
  },
  "fme_feature_type": "C__industrie_LDC__EMS2017"
}
Record 3db_hi: 1000000 · db_lo: 71
{
  "db_hi": "1000000",
  "db_lo": "71",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.738631002600697,
            48.565065186320275
          ],
          [
            7.738499544058762,
            48.56511147392801
          ],
          [
            7.738361087938208,
            48.56508229043779
          ],
          [
            7.738317554555599,
            48.56505152938486
          ],
          [
            7.738260419124681,
            48.564963762526
          ],
          [
            7.73832887233828,
            48.56487086622097
          ],
          [
            7.738340856527135,
            48.564864080022524
          ],
          [
            7.738472544091857,
            48.56482026801761
          ],
          [
            7.738611685753189,
            48.56485685200237
          ],
          [
            7.738616372465401,
            48.564859123323494
          ],
          [
            7.738706718723124,
            48.56494553347939
          ],
          [
            7.73866994982733,
            48.56503713584242
          ],
          [
            7.738631002600697,
            48.565065186320275
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.5649669361,
    "lon": 7.73848404217
  },
  "fme_feature_type": "C__industrie_LDC__EMS2017"
}
Record 4db_hi: 1000000 · db_lo: 71
{
  "db_hi": "1000000",
  "db_lo": "71",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.78931704701099,
            48.57566192175485
          ],
          [
            7.789318013145615,
            48.57575104937248
          ],
          [
            7.789256103645491,
            48.57566443719876
          ],
          [
            7.789308676203247,
            48.575651439261414
          ],
          [
            7.78931704701099,
            48.57566192175485
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.575688874,
    "lon": 7.78929671758
  },
  "fme_feature_type": "C__industrie_LDC__EMS2017"
}
Record 5db_hi: 1000000 · db_lo: 71
{
  "db_hi": "1000000",
  "db_lo": "71",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            7.717397293957337,
            48.58401391088461
          ],
          [
            7.717307043348089,
            48.58406106232316
          ],
          [
            7.7171685513979,
            48.5840318902259
          ],
          [
            7.717154628318809,
            48.58402377431608
          ],
          [
            7.717093078983284,
            48.58393617764937
          ],
          [
            7.717153602856235,
            48.58386999443471
          ],
          [
            7.717267147879865,
            48.583839004198936
          ],
          [
            7.717286071454288,
            48.58383393890917
          ],
          [
            7.717297840159397,
            48.58383775666879
          ],
          [
            7.717429415558366,
            48.58391566286949
          ],
          [
            7.71743619640396,
            48.58392223124526
          ],
          [
            7.717431149184285,
            48.58393443733152
          ],
          [
            7.717397293957337,
            48.58401391088461
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": 48.5839485395,
    "lon": 7.71726663702
  },
  "fme_feature_type": "C__industrie_LDC__EMS2017"
}

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_c_industrie_ldc_ems2017

License

  • ✓ Redistributable
  • ✓ Attribution required

Query examples

curl -s 'https://data.strasbourg.eu/api/explore/v2.1/catalog/datasets/bruit_c_industrie_ldc_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
81
Last upstream update
6 years ago
2020-12-07

License

No license declared upstream.

○ Documentation○ Data dictionary○ Versioning

Source: opendatasoft

Machine-readable & source

Bruit industriel 2017 - Dépassement des seuils (jour, soir, nuit) — live verification badge

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