Analysis grid for renaturation issues in urban areas of Île-de-FranceGrille d'analyse des enjeux à la renaturation sur les territoires urbains d'Île-de-France

Grille d'analyse des enjeux à la renaturation sur les territoires urbains d'Île-de-FranceAnalysis grid for renaturation issues in urban areas of Île-de-France

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This dataset supports analysis of renaturation (ecological restoration) issues across urban territories in the Île-de-France region, France. It translates three key issues into numerical scores: the lower the score associated with an issue, the stronger the interest in renaturing the area to address it. The grid allows priority renaturation zones to be identified by combining these scores across territories. It is published as part of the Île-de-France regional open data portal and is freely accessible without authentication, intended for use in urban planning and environmental policy related to greening and ecological restoration of urban land.Donnée permettant d'analyser les enjeux à la renaturation sur les territoires à l'aide de 3 enjeux traduits sous forme de score. Plus le score associé à un enjeu est bas, plus l'intérêt à renaturer la zone pour y répondre est fort. Il est ainsi possible de définir des zones de renaturation priori...

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Data schema (30 fields)

Filterable via the API (28)

objectidnum_125num_250num_500idfnudepinseesirentype_zoneevcouv_vegarbres_rzhmareshabitats_rscore_biodalea_icuinondationruissscore_ccvuln_icupm25car_iaucar_rbvacarence_evscore_scvst_areashast_lengths

Click a field to see example values.

Field	Type	Description
geo_point_2dGeo Point	geo_point_2d	Geographic center point coordinates of the grid cell.Geographic center point coordinates of the grid cell.
geo_shapeShape	geo_shape	Polygon geometry of the grid cell boundary.Polygon geometry of the grid cell boundary.
objectid	int	Internal unique identifier of the record.Internal unique identifier of the record.
num_125Num 125	int	Identifier of the 125m x 125m grid cell.Identifiant de la maille à l'échelle 125m*125m
num_250Num 250	int	Identifier of the 250m x 250m grid cell.Identifiant de la maille à l'échelle 250m*250m
num_500Num 500	int	Identifier of the 500m x 500m grid cell.Identifiant de la maille à l'échelle 500m*500m
idf	int	Indicator that the grid cell is located within Île-de-France.Indicator that the grid cell is located within Île-de-France.
nudep	int	Department code associated with the grid cell.Département associé à la maille
insee	int	INSEE commune code associated with the grid cell.Code INSEE associé à la maille
sirenSIREN (company)	int	SIREN code of the intercommunal body (EPT) the cell belongs to.EPT auquel la maille est associée
type_zoneType zone	int	Code classifying the type of zone of the grid cell.Code classifying the type of zone of the grid cell.
ev	int	Score for presence and size of green spaces in the cell.Espaces végétalisés 0 : absence d'espaces verts ; 1 : présence d'un espace verts de taille < 4,4 Ha ; 2 : présence d'un espaces verts de taille comprise entre 4,4 et 53,3 Ha ; 3 : présence d'un espace vert de taille supérieure à 53,3Ha
couv_vegCouv veg	int	Score for the share of vegetation cover in the cell.Couvert végétal 0 : couvert végétal < 25% ; 1 : couvert végétal >= 25% mais <45% ; 2 : couvert végétal >=45%
arbres_rArbres r	int	Score indicating presence of remarkable trees in the cell.Arbres remarquables 0 : absence d'arbres remarquables ; 1 : présence d'un ou plusieurs arbres remarquables dans la maille
zh	int	Score indicating presence of wetlands (Ecomos) in the cell.Zones humides : Ecomos 0 : absence de zones humides ; 2 : présence d'une zone humide dans la maille
mares	int	Score indicating presence of ponds in the cell.Mares 0 : absence de mares ; 1 : présence d'une ou plusieurs mares dans la maille
habitats_rHabitats r	int	Cumulative score of rare habitats (trees, wetlands, ponds) in the cell.Habitat rares Cumul des scores des différents habitats rares présents dans la maille (Score_ArbresR + Score_ZH + Score_Mares)
score_biodScore biod	int	Overall biodiversity stakes score for the grid cell.Overall biodiversity stakes score for the grid cell.
alea_icuAlea icu	int	Score of dominant daytime urban heat island hazard in the cell.Exposition à l'effet d'ICU > Indicateur Aléa jour Type d'aléa majoritaire dans la maille. 0 : effet fort ; 1 : effet moyen ; 2 : effet faible ; 3 : effet rafraichissant
inondation	int	Score of flood risk exposure in the cell.Exposition aux inondations Croisement des données MOS et zones inondables pour déduire un risque d'exposition aux inondations dans chaque maille. 0 : risque fort ; 1 risque moyen ; 2 : risque faible
ruiss	int	Score of runoff risk exposure in the cell.Exposition au ruissellement Croisement des données de pentes et d'imperméabilisation des sols pour déduire un risque d'exposition au ruissellement dans chaque maille. 0 : fortement exposée ; 1 moyennement exposée ; 2 : faiblement exposée.
score_ccScore cc	int	Cumulative climate change score (heat island, flood, runoff).Cumul des scores des différents critères : Alea_ICU + Inondation + Ruiss
vuln_icuVuln icu	int	Score of dominant population vulnerability to urban heat island.Type de vulnérabilité majoritaire dans la maille. 0 : vulnérabilité forte à très forte (classe 7 à 9) ; 1 : vulnérabilité moyenne (classe 4 à 6) ; 2 vulnérabilité faible (classe 1 à 3)
pm25	int	Score of exposure to PM2.5 air pollution in the cell.Exposition à la pollution par les PM2.5 dans la maille. 0 : PM2.5 >= 15µg/m³/an ; 1 : 10µg/m³/an < PM2.5 < 15 µg/m³/an ; 2 : PM2.5 <= 10µg/m³/an
car_iauCar iau	int	Score combining two green-space deficiency indicators from the plan vert.Les deux indicateurs sont cumulés, permettant de différencier les zones ne présentant qu'un seul type de carence (dans le cadre du plan vert), celles présentant les deux, et celles n'en présentant aucune. Ils sont ensuite reclassé pour être traduit en score : 0 = les deux types de carence sont présentes sur la zone ; 1 = un seul type de carence présente sur la zone ; 2 = pas de carence
car_rbvaCar rbva	int	Score of vegetation index deficiency in the cell.Indice de végétation 0 : couvert végétal < 30% ; 1 : couvert végétal >= 30% mais <45% ; 2 : couvert végétal >=45%
carence_evCarence ev	int	Combined and reclassified green-space deficiency score.Les champs "Car_IAU" et "Car_RBVA" sont additionnés et reclassés pour être contenu entre 1 et 2 0 : score de 0 ou 1 ; 1 : score de 2 ; 2 : score de 3 ou plus
score_scvScore scv	int	Cumulative health and living environment score (deficiency, PM2.5, heat vulnerability).Cumul des scores des différents critères : Carence_EV + PM25 + Vuln_ICU
st_areashaSt areasha	int	Area of the grid cell shape.Area of the grid cell shape.
st_lengthsSt lengths	int	Perimeter length of the grid cell shape.Perimeter length of the grid cell shape.

Schema captured from opendatasoft 2 days ago.

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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 1ev: — · zh: 0

{
  "ev": null,
  "zh": 0,
  "idf": 1,
  "pm25": 1,
  "insee": 91338,
  "mares": 0,
  "nudep": 91,
  "ruiss": null,
  "siren": 249100074,
  "car_iau": 1,
  "num_125": 614775,
  "num_250": 98042,
  "num_500": 24394,
  "alea_icu": null,
  "arbres_r": 0,
  "car_rbva": null,
  "couv_veg": null,
  "objectid": 333725,
  "score_cc": null,
  "vuln_icu": null,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            2.073366488938075,
            48.65656665569214
          ],
          [
            2.073346573399836,
            48.65769092426896
          ],
          [
            2.075043585458624,
            48.657704106490165
          ],
          [
            2.075063464531536,
            48.65657983764243
          ],
          [
            2.073366488938075,
            48.65656665569214
          ]
        ]
      ]
    },
    "properties": {}
  },
  "score_scv": null,
  "type_zone": 3,
  "carence_ev": null,
  "habitats_r": 0,
  "inondation": 2,
  "score_biod": null,
  "st_areasha": 15625,
  "st_lengths": 500,
  "geo_point_2d": {
    "lat": 48.65713538303662,
    "lon": 2.074205028044835
  }
}

Record 2ev: 2 · zh: 2

{
  "ev": 2,
  "zh": 2,
  "idf": 1,
  "pm25": 1,
  "insee": 91534,
  "mares": 0,
  "nudep": 91,
  "ruiss": 0,
  "siren": 200056232,
  "car_iau": 1,
  "num_125": 721061,
  "num_250": 110112,
  "num_500": 27546,
  "alea_icu": 3,
  "arbres_r": 0,
  "car_rbva": 1,
  "couv_veg": 1,
  "objectid": 424727,
  "score_cc": 5,
  "vuln_icu": 2,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            2.149911793866402,
            48.75045964715651
          ],
          [
            2.14989349054783,
            48.751583838036034
          ],
          [
            2.151593572587205,
            48.75159592938603
          ],
          [
            2.151611839307601,
            48.75047173825797
          ],
          [
            2.149911793866402,
            48.75045964715651
          ]
        ]
      ]
    },
    "properties": {}
  },
  "score_scv": 3,
  "type_zone": 6,
  "carence_ev": 0,
  "habitats_r": 2,
  "inondation": 2,
  "score_biod": 5,
  "st_areasha": 15625,
  "st_lengths": 500,
  "geo_point_2d": {
    "lat": 48.75102779022586,
    "lon": 2.1507526740429745
  }
}

Record 3ev: 0 · zh: 0

{
  "ev": 0,
  "zh": 0,
  "idf": 1,
  "pm25": 1,
  "insee": 77067,
  "mares": 0,
  "nudep": 77,
  "ruiss": 1,
  "siren": 200059228,
  "car_iau": 0,
  "num_125": 503725,
  "num_250": 179063,
  "num_500": 44730,
  "alea_icu": 2,
  "arbres_r": 0,
  "car_rbva": 1,
  "couv_veg": 1,
  "objectid": 240855,
  "score_cc": 5,
  "vuln_icu": 2,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            2.600209720721243,
            48.56167514854827
          ],
          [
            2.600201143682874,
            48.56279956787618
          ],
          [
            2.601895177865179,
            48.56280524896506
          ],
          [
            2.601903718562017,
            48.56168082952043
          ],
          [
            2.600209720721243,
            48.56167514854827
          ]
        ]
      ]
    },
    "properties": {}
  },
  "score_scv": 5,
  "type_zone": 6,
  "carence_ev": 2,
  "habitats_r": 0,
  "inondation": 2,
  "score_biod": 1,
  "st_areasha": 15625,
  "st_lengths": 500,
  "geo_point_2d": {
    "lat": 48.562240200737655,
    "lon": 2.60105244019188
  }
}

Record 4ev: 2 · zh: 0

{
  "ev": 2,
  "zh": 0,
  "idf": 1,
  "pm25": 2,
  "insee": 78335,
  "mares": 0,
  "nudep": 78,
  "ruiss": 0,
  "siren": 200059889,
  "car_iau": 0,
  "num_125": 1011392,
  "num_250": 50081,
  "num_500": 12465,
  "alea_icu": 3,
  "arbres_r": 0,
  "car_rbva": 2,
  "couv_veg": 2,
  "objectid": 667244,
  "score_cc": 5,
  "vuln_icu": 2,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            1.75453869725713,
            49.00219975938521
          ],
          [
            1.754511751796181,
            49.00332361891957
          ],
          [
            1.756219957700459,
            49.0033413350489
          ],
          [
            1.756246866217536,
            49.00221747515016
          ],
          [
            1.75453869725713,
            49.00219975938521
          ]
        ]
      ]
    },
    "properties": {}
  },
  "score_scv": 6,
  "type_zone": 2,
  "carence_ev": 2,
  "habitats_r": 0,
  "inondation": 2,
  "score_biod": 4,
  "st_areasha": 15625,
  "st_lengths": 500,
  "geo_point_2d": {
    "lat": 49.002770549151435,
    "lon": 1.7553793181919197
  }
}

Record 5ev: — · zh: 0

{
  "ev": null,
  "zh": 0,
  "idf": 1,
  "pm25": 1,
  "insee": 77205,
  "mares": 0,
  "nudep": 77,
  "ruiss": null,
  "siren": 200072130,
  "car_iau": 2,
  "num_125": 1031226,
  "num_250": 215879,
  "num_500": 53968,
  "alea_icu": null,
  "arbres_r": 0,
  "car_rbva": null,
  "couv_veg": null,
  "objectid": 682802,
  "score_cc": null,
  "vuln_icu": null,
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            2.837631154665688,
            49.02541194725838
          ],
          [
            2.83762764011447,
            49.0265359194265
          ],
          [
            2.839336818107773,
            49.02653821851421
          ],
          [
            2.839340295664023,
            49.025414246298794
          ],
          [
            2.837631154665688,
            49.02541194725838
          ]
        ]
      ]
    },
    "properties": {}
  },
  "score_scv": null,
  "type_zone": 3,
  "carence_ev": null,
  "habitats_r": 0,
  "inondation": 2,
  "score_biod": null,
  "st_areasha": 15625,
  "st_lengths": 500,
  "geo_point_2d": {
    "lat": 49.02597508490185,
    "lon": 2.838483977131369
  }
}

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

Verification Status

Using the API

Configuration

Base URL: https://data.iledefrance.fr/api/explore/v2.1/catalog/datasets/grille-analyse-enjeux-renaturation

License

Licence Ouverte 2.0 (France / Etalab)Open

✓ Redistributable
✓ Attribution required

Query examples

curl -s 'https://data.iledefrance.fr/api/explore/v2.1/catalog/datasets/grille-analyse-enjeux-renaturation/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

10 000 req/day

per ipmeasured

observed 2 days ago

Dataset

Volume & freshness

Records

780k

780412

Last upstream update

3 years ago

2023-07-04

License

No license declared upstream.

○ Documentation○ Data dictionary○ Versioning

Source: opendatasoft

Machine-readable & source

JSON

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