Land Use Land Cover High Resolution Map (5-m) for Côte-d’Or (21) (ICPSR doi:10.15454/ECLYGT)
(Carte à haute résolution (5-m) de l’occupation du sol urbain et rural du département de Côte-d’Or (21))

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Part 2: Study Description
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Document Description

Citation

Title:

Land Use Land Cover High Resolution Map (5-m) for Côte-d’Or (21)

Identification Number:

doi:10.15454/ECLYGT

Distributor:

Portail Data INRAE

Date of Distribution:

2020-01-10

Version:

2

Bibliographic Citation:

Hilal, Mohamed, 2020, "Land Use Land Cover High Resolution Map (5-m) for Côte-d’Or (21)", https://doi.org/10.15454/ECLYGT, Portail Data INRAE, V2

Study Description

Citation

Title:

Land Use Land Cover High Resolution Map (5-m) for Côte-d’Or (21)

Alternative Title:

Carte à haute résolution (5-m) de l’occupation du sol urbain et rural du département de Côte-d’Or (21)

Identification Number:

doi:10.15454/ECLYGT

Authoring Entity:

Hilal, Mohamed (INRAE - Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement)

Other identifications and acknowledgements:

Joly, Daniel

Producer:

Hilal, Mohamed

Roy, Damien

Distributor:

Portail Data INRAE

Access Authority:

Hilal, Mohamed

Depositor:

Hilal, Mohamed

Date of Deposit:

2020-01-10

Study Scope

Keywords:

Other, spatial data, land cover mapping

Abstract:

The LULC HRL Map is produced from a combination of multi-sources data: the French national topographic database; the Land Parcel Identification System (LPIS) database; and Corine Land Cover.

Country:

France

Geographic Coverage:

Bourgogne-Franche-Comté, Côte-d'Or

Geographic Unit(s):

meters

Geographic Bounding Box:

  • West Bounding Longitude: 780330
  • East Bounding Longitude: 890290
  • South Bounding Latitude: 6645776
  • North Bounding Latitude: 6771336

Kind of Data:

Dataset

Notes:

The LULC HRL Map is produced from a combination of multi-sources data: the French national topographic database (Institut national de l’information géographique et forestière, the French national geographic institute); the Land Parcel Identification System (LPIS) database (Agency for Services and Payment, French public institution responsible for the implementation of national and European public policies; Integrated Administration and Control System, European Union); and Corine Land Cover (European Environment Agency, Joint Research Center, European Union). The topographic database contains a land cover description employed for topographic map production at a scale of 1:25 000, with a minimum unit of collection of approximately 8 ha. The information is relatively precise on the contours of urban areas (buildings), road and rail infrastructures, hydrography, and trees and shrubs; however, it does not make it possible to distinguish the land uses within the agricultural, forested, or natural areas. The LPIS database, which draws on the digital cadastral database (1:500–1:5000), allows us to identify those agricultural areas for which subsidies are sought under the European Common Agricultural Policy (CAP). It was used to determine the agricultural land-use (grass-like vegetation and arable land) on the scale of cadastral parcels. Corine Land Cover (CLC) is thematically much richer, in particular in agri- cultural areas, but its spatial resolution, which is rather coarse (approximately 1:100 000), means it cannot identify the nature of a polygon of less than 25 ha. Despite its rather coarse resolution, CLC has a thematically richer land-use nomenclature than can be used to refine plant cover. The land-cover information layer was constructed in two steps. The first was to generate a simplified geometry of land use in vector form (polygons and lines). The operation begins by detecting the “polygonal skeleton” that integrates roads, railways, and the hydrographic network attributing to them a footprint proportional to their width. Next are added (1) agricultural surface features from the LPIS (field, meadow, orchard, other agriculture use); (2) plant-covered areas, mostly forest and orchard; and (3) artificialized surfaces (buildings, quarries, parking areas, etc.). Each addition is made by masking and expansion so as to approximate the “polygonal skeleton”. The features not described in the topographic database and the LPIS are categorized as “unidentified polygons”. Some of this class is marked down as grassland-lawn using CLC classes “321” (Natural grasslands) and “231” (Pastures). Processing is done with the PostGIS functionalities: intersection, union, dilation, erosion, etc. of polygons or lines (PostGIS, 2018). This stage enables eight land-use categories to be defined: (1) urban footprints, (2) fields, (3) meadows, (4) forests, (5) orchards, (6) rivers and water bodies, (7) road and rail infrastructure footprints, (8) unidentified polygons. This first vectorial geometric model is changed into a 5m resolution raster layer and then supplemented to produce a land-use layer com- patible with the landscape analysis contemplated. Categories (4), (6) and (7) describing relatively homogeneous and straightforward landscape features were kept unchanged. The improvement described below was primarily for heterogeneous and complex landscape features (categories (1), (2), (3) and (5)) that are replaced by simple landscape objects (buildings, mineral surfaces, copses, fields, grass-covered areas, etc.). The improvement also covers pixels in category (8). Pixels of the urban footprint (1) are differentiated into three types of landscape items: the built area, parking areas, and urban plant cover. The built area is incrusted by distinguishing its height and function: (11, LRM) Low-rise Residential or Mixed buildings (< 12m∼1–2 storeys); (12, HRM) High-rise Residential or Mixed buildings (≥12m∼3 storeys and more); (13, ICF) Industrial or Commercial buildings and other Facilities; (14) agricultural buildings. Parking areas were also created around some buildings and classified as category (7): a 5m (1 pixel) buffer around HRM polygons and ICF polygons between 50 and 999m2; a 25m buffer for ICF polygons of 1000m2 (5 pixels) and more. The buffer sizes were established from existing planning and building codes. Non-built and non-parking areas in the urban footprint are converted into plant cover in the following proportions: grass 50% of pixels; Trees 25%; shrubs and bushes 25%. These proportions are based on the visual identification and quantification of green areas/ expanses in built the environment using orthophoto images. This is done by first converting non-built and non-parking areas into grass pixels and then drawing tree pixels and shrub and bush pixels at random. For the field (2) and meadow (3) categories identified with tree cover (presence of trees in CLC), 10% of randomly drawn pixels are converted into trees. The pixels classified as orchards (5) and that are within a polygon classified as vineyard (221) in CLC are reclassified as vineyard. The remaining pixels are first converted into grass and then into shrubs and bushes by randomly drawing 70% of the pixels. Pixels in category (8), “unidentified polygons”, are reclassified by comparison with the CLC polygons.

Methodology and Processing

Sources Statement

Data Sources:

French national topographic database (Institut national de l’information géographique et forestière, the French national geographic institute)

Land Parcel Identification System (LPIS) database (Agency for Services and Payment, French public institution responsible for the implementation of national and European public policies; Integrated Administration and Control System, European Union)

Corine Land Cover (European Environment Agency, Joint Research Center, European Union)

Data Access

Citation Requirement:

To use or reference this resource, specify the following information: Hilal, Mohamed, 2020, "Land Use Land Cover High Resolution Map (5-m) for Côte-d’Or (21)", https://doi.org/10.15454/ECLYGT, Portail Data INRAE

Notes:

CC0 Waiver

Other Study Description Materials

Related Publications

Citation

Identification Number:

10.1016/j.ufug.2018.03.020

Bibliographic Citation:

Hilal, Mohamed ; Joly, Daniel ; Roy, Damien ; Vuidel, Gilles, 2018, « Visual structure of landscapes seen from built environonment ». Urban Forestry & Urban Greening, 32.

Citation

Identification Number:

10.1016/j.landurbplan.2017.03.003

Bibliographic Citation:

Caruso, Geoffrey ; Hilal, Mohamed ; Thomas, Isabelle, 2017, « Measuring urban forms from inter-building distances: Combining MST graphs with a Local Index of Spatial Association ». Landscape and Urban Planning 163, 80-89.

Citation

Identification Number:

10.1016/j.landusepol.2016.01.005

Bibliographic Citation:

Hilal, Mohamed ; Martin, Elsa ; Piguet, Virginie, 2016, « Prediction of the purchase cost of agricultural land: The example of Côte-d’Or, France ». Land Use Policy, 52, 464-476.

Other Study-Related Materials

Label:

mosfinal0005a.R

Text:

Notes:

type/x-r-syntax

Other Study-Related Materials

Label:

mosfinal0005a.tfw

Notes:

application/octet-stream

Other Study-Related Materials

Label:

mosfinal0005a.tif

Text:

Land Use Land Cover High Resolution Raster Map

Notes:

image/tiff

Other Study-Related Materials

Label:

mosfinal0005a.txt.txt

Text:

The LULC HRL contains 11 land cover categories

Notes:

text/plain