Datasets

Derived from the neighbourhoods dataset.

Origin of the data: Madrid City Council (or, where appropriate, administrative body, body or entity in question)

Blocks

The Copernicus land monitoring products and services are made available on a principle of full, open and free access, as established by the Commission Delegated Regulation (EU) No 1159/2013 of 12 July 2013. Free, full and open access to the products and services of the Copernicus Land Monitoring Service is made on the conditions that:

When distributing or communicating Copernicus Land Monitoring Service products and services (data, software scripts, web services, user and methodological documentation and similar) to the public, users shall inform the public of the source of these products and services.
Where the Copernicus Land Monitoring Service products and services have been adapted or modified by the user, the user shall clearly state this.
Users shall make sure not to convey the impression to the public that the user’s activities are officially endorsed by the European Union.

Urban Atlas Land Cover/Land Use 2018 (vector), Europe, 6-yearly. European Union’s Copernicus Land Monitoring Service information, https://land.copernicus.eu/en/products/urban-atlas/urban-atlas-2018. https://doi.org/10.2909/fb4dffa1-6ceb-4cc0-8372-1ed354c285e6 (Accessed on DD.MM.YYYY)

Premises

Origin of the data: Madrid City Council (or, where appropriate, administrative body, body or entity in question)

Description: Microdata file of the census of premises and activities of the Madrid City Council, classified according to their type of access (street door or grouped), situation (open, closed…) and indication of the economic activity exercised and the hospitality and restaurant terraces that appear registered in said census.

Preprocessing performed per: https://github.com/songololo/ua-dataset-madrid.

Key columns:

Column	Description
`local_distr_desc`	District name
`local_neighb_desc`	Neighbourhood name
`section_id`	Activity section code (e.g., I = hospitality, R = recreation)
`section_desc`	Activity section description
`division_id`	Activity division code
`division_desc`	Activity division description
`epigraph_id`	Specific activity code
`epigraph_desc`	Specific activity description (e.g., RESTAURANTE)

Overture Maps Buildings

License for theme: ODbL

© OpenStreetMap contributors. Available under the Open Database License.
Esri Community Maps contributors. Available under CC BY 4.0.
Global ML Building Footprints. Licensed by Microsoft under the Open Database License.
Google Open Buildings. Available under CC BY 4.0.
USGS 3D Elevation Program Digital Elevation Program.
Qian Shi, et al. A First High-quality Vector Data of Buildings in East Asian Countries Based on a Comprehensive Large-scale Mapping Framework. Zenodo, 22 July 2023, doi:10.5281/zenodo.8174931. Available under CC BY 4.0.

Key columns:

Column	Description
`mean_height`	Average building height in metres (where available)
`area`	Footprint area in square metres
`perimeter`	Footprint perimeter in metres
`compactness`	Compactness ratio (area relative to perimeter)
`orientation`	Orientation angle in degrees
`volume`	Estimated building volume (height x area, where available)
`floor_area_ratio`	Floor area ratio
`form_factor`	Building form factor
`corners`	Number of corners in the footprint
`shape_index`	Shape index metric
`fractal_dimension`	Fractal dimension of the footprint boundary

Overture Maps Infrastructure

License for theme: ODbL

© OpenStreetMap contributors. Available under the Open Database License.
Data from the Daylight Map Distribution
ESA WorldCover. Available under CC BY 4.0 DEED.
Data products from ETOPO1. Available under Open Data Commons Public Domain Dedication and License.
Data from GLOBathy. Available under CC0 1.0 (assumed).

Streets

Source (CNIG/IGN - Redes de Transporte - Madrid province)

License (ign.es)

Cite: Attribute IGN (Instituto Geográfico Nacional de España).

Description: Road network (Red Viaria) for Madrid province from the CNIG/IGN Redes de Transporte dataset. Layer rt_tramo_vial containing road segments with classification, surface, lane, and naming attributes.

Preprocessing: Download RT_MADRID_gpkg.zip from CNIG Centro de Descargas. Extract red_viaria.gpkg, layer rt_tramo_vial. Reproject from EPSG:4258 to EPSG:25830. Clip to 20km buffered bounds. Retain clased (road class) and nombre (road name) attributes only. Set coordinate grid precision to 1m and simplify geometries to 1m tolerance.

Further preprocessing performed per: https://github.com/songololo/ua-dataset-madrid.

Key columns:

Column	Description
`clased`	Road classification (e.g., Urbano)
`nombre`	Street name

Census