Rail noise 2017 - Threshold exceedances (day, evening, night)Bruit ferroviaire 2017 - Dépassement des seuils (jour, soir, nuit)
Bruit ferroviaire 2017 - Dépassement des seuils (jour, soir, nuit)Rail noise 2017 - Threshold exceedances (day, evening, night)
API providing a type C map dataset identifying areas within the Strasbourg metropolitan area, France, where regulatory railway noise limits are exceeded, based on the Lden indicator (day, evening, night), for the 2017 reference year. Thresholds are set at 73 dB(A) for conventional lines and 68 dB(A) for high-speed lines. The dataset is published via the Strasbourg open data portal and is intended to provide comprehensive information on rail-related noise exposure in the area, useful for environmental assessment, urban planning, and public information purposes.Carte de type C indiquant les zones où les valeurs limites réglementaires pour le bruit ferroviaire pour l'indicateur Lden (jour, soir, nuit) sont dépassés : 73 dB(A) pour les lignes conventionnelles 68 dB(A) pour les lignes à grande vitesse Millésime 2017 Une information complète sur le bruit es...
Trust score
How is this computed?Weighted across five axes. Tap a ring for what it measures.
Data schema (5 fields)
Click a field to see example values.
| Field | Type | Description |
|---|---|---|
| geo_point_2dGeo Point | geo_point_2d | Geographic centroid coordinates of the zone.Geographic centroid coordinates of the zone. |
| geo_shapeShape | geo_shape | Polygon geometry delimiting the noise exceedance zone.Polygon geometry delimiting the noise exceedance zone. |
| db_loDb lo | text | Lower bound of the noise level range in dB(A).Lower bound of the noise level range in dB(A). |
| db_hiDb hi | text | Upper bound of the noise level range in dB(A).Upper bound of the noise level range in dB(A). |
| fme_feature_typeFme feature type | text | Internal FME feature type code identifying the dataset source.Internal FME feature type code identifying the dataset source. |
Schema captured from opendatasoft 1 day 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: 99 · db_lo: 73
{
"db_hi": "99",
"db_lo": "73",
"geo_shape": {
"type": "Feature",
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
7.71558756270139,
48.57345584745886
],
[
7.715517852498555,
48.57350442001116
],
[
7.715378418034923,
48.57346471133995
],
[
7.715376974076656,
48.573464405617266
],
[
7.715237312978952,
48.57340689610385
],
[
7.715146816449832,
48.57338366007975
],
[
7.715233822208965,
48.573369066917245
],
[
7.715327721156429,
48.57328621008278
],
[
7.715360421428103,
48.57326968906465
],
[
7.71546251632939,
48.57328073219371
],
[
7.715399350352818,
48.57337339773749
],
[
7.715510165735196,
48.57342112424526
],
[
7.71557161756182,
48.57336639691433
],
[
7.715639049279782,
48.57334650346967
],
[
7.715725953904735,
48.5733601245709
],
[
7.71564587670916,
48.57342048536551
],
[
7.71558756270139,
48.57345584745886
]
]
]
},
"properties": {}
},
"geo_point_2d": {
"lat": 48.5733920793,
"lon": 7.71543404167
},
"fme_feature_type": "C__fer_LDC__EMS2017"
}Record 2db_hi: 99 · db_lo: 73
{
"db_hi": "99",
"db_lo": "73",
"geo_shape": {
"type": "Feature",
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
7.719163522494824,
48.574481748883194
],
[
7.719143546102015,
48.57454026849578
],
[
7.719003230103032,
48.57449107995967
],
[
7.718985687645945,
48.574488981325516
],
[
7.719002812185358,
48.57448655474414
],
[
7.719108257761518,
48.574393897720924
],
[
7.719127556362588,
48.574367136237896
],
[
7.719264498108037,
48.57437979254777
],
[
7.719282747603041,
48.57438680112248
],
[
7.719265600171282,
48.57439172505661
],
[
7.719163522494824,
48.574481748883194
]
]
]
},
"properties": {}
},
"geo_point_2d": {
"lat": 48.5744455403,
"lon": 7.71913343635
},
"fme_feature_type": "C__fer_LDC__EMS2017"
}Record 3db_hi: 99 · db_lo: 73
{
"db_hi": "99",
"db_lo": "73",
"geo_shape": {
"type": "Feature",
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
7.722704521190178,
48.63362222357407
],
[
7.722704186641416,
48.63363003739534
],
[
7.722701998856143,
48.63362232611421
],
[
7.722693291095212,
48.63353258298571
],
[
7.722672872059449,
48.633443315951055
],
[
7.722545867145219,
48.63338807842253
],
[
7.722436887314553,
48.63336281202959
],
[
7.72243149713331,
48.63327293403117
],
[
7.722448804669654,
48.633182133346786
],
[
7.722466711238114,
48.6330913083029
],
[
7.722486464986112,
48.63300040816001
],
[
7.722503055010306,
48.63292539578402
],
[
7.722512583328142,
48.63299934640709
],
[
7.722553869237204,
48.633087765187206
],
[
7.722660176416605,
48.6331544248235
],
[
7.722749443997654,
48.63316991165535
],
[
7.722746766924357,
48.633260117627515
],
[
7.722731621269105,
48.63335083048639
],
[
7.722711525843842,
48.63344174456168
],
[
7.722707675632382,
48.63353199821222
],
[
7.722704521190178,
48.63362222357407
]
]
]
},
"properties": {}
},
"geo_point_2d": {
"lat": 48.6332566862,
"lon": 7.72258789441
},
"fme_feature_type": "C__fer_LDC__EMS2017"
}Record 4db_hi: 99 · db_lo: 73
{
"db_hi": "99",
"db_lo": "73",
"geo_shape": {
"type": "Feature",
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
7.707500226462062,
48.56855854744487
],
[
7.707462861188788,
48.568599270963894
],
[
7.707439862789228,
48.568560996637885
],
[
7.707456979091678,
48.568535415486124
],
[
7.707500226462062,
48.56855854744487
]
]
]
},
"properties": {}
},
"geo_point_2d": {
"lat": 48.5685646737,
"lon": 7.70746688884
},
"fme_feature_type": "C__fer_LDC__EMS2017"
}Record 5db_hi: 99 · db_lo: 73
{
"db_hi": "99",
"db_lo": "73",
"geo_shape": {
"type": "Feature",
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
7.719436098544515,
48.574560761635674
],
[
7.719419007155401,
48.57458265038292
],
[
7.719282010628009,
48.57456940740584
],
[
7.71926897465732,
48.574567558859925
],
[
7.719281681256016,
48.574565841180416
],
[
7.719388414017348,
48.574472602279926
],
[
7.71940587344145,
48.574440450867925
],
[
7.719447876018433,
48.57447018381695
],
[
7.719436098544515,
48.574560761635674
]
]
]
},
"properties": {}
},
"geo_point_2d": {
"lat": 48.5745264887,
"lon": 7.71938443025
},
"fme_feature_type": "C__fer_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_fer_ldc_ems2017
License
- ✓ Redistributable
- ✓ Attribution required
Query examples
curl -s 'https://data.strasbourg.eu/api/explore/v2.1/catalog/datasets/bruit_c_fer_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.
Rate limits
Dataset
Volume & freshness
License
No license declared upstream.
Source: opendatasoft
Machine-readable & source
Embed this badge in a README or wiki — it always shows the latest verification state and quality tier.