OGC i3s 3D Object Scene layer of the 3D BAG for the city of Dordrecht from the 3D BAG by 3D geoinformation research group, TU Delft. For more information on the BAG 3D copyright, please check this copyright page.

De 3D BAG is een up-to-date landsdekkende dataset met 3D gebouwmodellen van Nederland. De 3D BAG is open data. Het bevat 3D modellen op verscheidene detailniveaus welke zijn gegenereerd door de combinatie van twee open datasets: de pand-gegevens uit de BAG en de hoogtegegevens uit de AHN. De 3D BAG wordt regelmatig geüpdatet met de meest recente openlijk beschikbare pand- en hoogtegegevens.De 3D BAG is eveneens een plek voor experimenten. We gebruiken de data zelf ook om nieuwe ideeën te testen in onderzoek en onderwijs binnen de 3D geoinformation onderzoeksgroep. Gebaseerd op ervaringen met de data verbeteren we constant onze methoden, en door onze eigen service te ontwikkelen en in beheer te houden, behouden we de volledige controle over het gehele proces van invoerdata, voorbewerking en reconstructie tot querying en het gebruik van de gereconstrueerde 3D data voor stedelijke toepassingen.Bron: https://docs.3dbag.nl/nl/

This dataset contains the calculated metrics of 3D buildings in four major cities of the Netherlands, used for our paper: "Anna Labetski, Stelios Vitalis, Filip Biljecki, Ken Arroyo Ohori, and Jantien Stoter, 3D Building Metrics for Urban Morphology, 2022, International Journal of Geographical Information Science" The metrics were computed against 648 tiles of 3D BAG version 21.09.8, containing 824531 buildings in four major cities: Amsterdam, The Hague, Rotterdam, and Utrecht. The list of tiles is available in tiles.tab. The metrics are available in three CSVs, one for every LoD available for every building (LoD1.2, LoD1.3 and LoD2), each with the respective filename. There are also three tables with the comparative analysis between the (boolean) volume of different LoDs.

This dataset contains raw GIS data sourced from the BAG (Basisregistratie Adressen en Gebouwen; Registry of Addresses and Buildings). It provides comprehensive information on buildings, including advanced height data and administrative details. It also contains geographic divisions within The Hague. Additionally, the dataset incorporates energy label data, offering insights into the energy efficiency and performance of these buildings. This combined dataset serves as the backbone of a Master's thesis in Industrial Ecology, analysing residential and office cooling and its environmental impacts in The Hague, Netherlands. The codebase of this analysis can be found in this Github repository: https://github.com/simonvanlierde/msc-thesis-ie

The dataset includes a background research spreadsheet containing supporting calculations. It also presents geopackages with results from the cooling demand model (CDM) for various scenarios: Status quo (SQ), 2030, and 2050 scenarios (Low, Medium, and High)

Background research data

The background_research_data.xlsx spreadsheet contains comprehensive background research calculations supporting the shaping of input parameters used in the model. It contains several sheets:

• Cooling Technologies: Details the various cooling technologies examined in the study, summarizing their characteristics and the market penetration mixes used in the analysis.
• LCA Results of Ventilation Systems: Provides an overview of the ecoinvent processes serving as proxies for the life-cycle impacts of cooling equipment, along with calculations of the weight of cooling systems and contribution tables from the LCA-based assessment.
• Material Scarcity: A detailed examination of the critical raw material content in the material footprint of ecoinvent processes, representing cooling equipment.
• Heat Plans per Neighbourhood: Forecasts of future heating solutions for each neighbourhood in The Hague.
• Building Stock: Analysis of the projected growth trends in residential and office building stocks in The Hague. AC Market: Market analysis covering air conditioner sales in the Netherlands from 2002 to 2022.
• Climate Change: Computations of climate-related parameters based on KNMI climate scenarios.
• Electricity Mix Analysis: Analysis of future projections for the Dutch electricity grid and calculations of life-cycle carbon intensities of the grid.

Input data

Geographic divisions

• The outline of The Hague municipality through the Municipal boundaries (Gemeenten) layer, sourced from the Administrative boundaries (Bestuurlijke Gemeenten) dataset on the PDOK WFS service.
• District (Wijken) and Neighbourhood (Buurten) layers were downloaded from the PDOK WFS service (from the CBS Wijken en Buurten 2022 data package) and clipped to the outline of The Hague.
• The 4-digit postcodes layer was downloaded from PDOK WFS service (CBS Postcode4 statistieken 2020) and clipped to The Hague's outline. The postcodes within The Hague were subsequently stored in a csv file.
• The census block layer was downloaded from the PDOK WFS service (from the CBS Vierkantstatistieken 100m 2021 data package) and also clipped to the outline of The Hague.
• These layers have been combined in the GeographicDivisions_TheHague GeoPackage.

BAG data

• BAG data was acquired through the download of a BAG GeoPackage from the BAG ATOM download page.
• In the resulting GeoPackage, the Residences (Verblijfsobject) and Building (Pand) layers were clipped to match The Hague's outline.
• The resulting residence data can be found in the BAG_buildings_TheHague GeoPackage.

3D BAG

• Due to limitations imposed by the PDOK WFS service, which restricts the number of downloadable buildings to 10,000, it was necessary to acquire 145 individual GeoPackages for tiles covering The Hague from the 3D BAG website.
• These GeoPackages were merged using the ogr2ogr append function from the GDAL library in bash.
• Roof elevation data was extracted from the LoD 1.2 2D layer from the resulting GeoPackage.
• Ground elevation data was obtained from the Pand layer.
• Both of these layers were clipped to match The Hague's outline.
• Roof and ground elevation data from the LoD 1.2 2D and Pand layers were joined to the Pand layer in the BAG dataset using the BAG ID of each building.
• The resulting data can be found in the BAG_buildings_TheHague GeoPackage.

Energy labels

• Energy labels were downloaded from the Energy label registry (EP-online) and stored in energy_labels_TheNetherlands.csv.

UHI effect data

• A bitmap with the UHI effect intensity in The Hague was retrieved from the from the Dutch Natural Capital Atlas (Atlas Natuurlijk Kapitaal) and stored in UHI_effect_TheHague.tiff.

Output data

• The residence-level data joined to the building layer is contained in the BAG_buildings_with_residence_data_full GeoPackage.
• The results for each building, according to different scenarios, are compiled in the buildings_with_CDM_results_[scenario]_full GeoPackages. The scenarios are abbreviated as follows:
  • SQ: Status Quo, covering the 2018-2022 reference period.
  • 2030: An average scenario projected for the year 2030.
  • 2050_L: A low-impact, best-case scenario for 2050.
  • 2050_M: A medium-impact, moderate scenario for 2050.
  • 2050_H: A high-impact, worst-case scenario for 2050.

De 3D BAG is een actuele dataset met daarin de 3D-gebouwen van Nederland. De 3D BAG is open data. Het bevat 3D-modellen die worden gegenereerd door twee open datasets te combineren: de gebouwgegevens uit de BAG en de hoogtegegevens uit de AHN. De 3D BAG wordt regelmatig bijgewerkt, zodat deze up-to-date blijft met de nieuwste vrij beschikbare gebouwenvoorraad en hoogte-informatie.

Latest (near-live) version of the BAG data. Parent item: 3D Registration of Buildings and Addresses (BAG) The 3D BAG is a register of addresses and buildings of the Netherlands, including building height information and related quality metrics. The data set is updated every month, keeping it up-to-date with the latest building stock and elevation information. The 3D BAG is generated from two data sources, the Dutch national register of addresses and buildings (Basisregistraties Adressen en Gebouwen (BAG)) and the national elevation model (AHN).

Snapshot of the BAG data at 2020-05-13. Parent item: 3D Registration of Buildings and Addresses (BAG) The 3D BAG is a register of addresses and buildings of the Netherlands, including building height information and related quality metrics. The data set is updated every month, keeping it up-to-date with the latest building stock and elevation information. The 3D BAG is generated from two data sources, the Dutch national register of addresses and buildings (Basisregistraties Adressen en Gebouwen (BAG)) and the national elevation model (AHN).

Actualiteit: Maandelijks geactualiseerd; zie het ArcGIS Online item van de Bebouwing-3D laag.Deze 3D-Viewer App bevat verschillende 3D-lagen en 2D-lagen om de gebouwen in de gemeente en hun eigenschappen in hun 3D context te laten zien. 3D-lagen: Bebouwing 3D, Windturbines 3D, Bomen 3D. 2D-lagen: Bebouwing 2D, Gemeente Midden-Groningen. Niet alle gebouwen hebben een geometrie in de 3D BAG. Daarom moeten we ook een 2D bebouwing laag bewaren. De reden hiervoor is dat de 3D BAG is met AHN4 en AHN3 gemaakt en sinds het moment van het inwinnen van die gegevens hebben er veranderingen plaatsgevonden in de gebouwde omgeving.De laag Bebouwing 3D is een zogenaamde groepslaag. Binnen deze groep bevinden zich verschillende lagen, die elk een ander kenmerk van de gebouwen laten zien. Bijvoorbeeld energielabels, bouwjaar en de locatie van monumenten.Al deze informatie is samengevat in de gebouwgeometrieën zelf. Dit betekent dat u, door op elk gebouw te klikken, alle eigendommen ervan tegelijkertijd kunt zien.Dit project is sterk geïnspireerd door de 'Digitale Tweelingstad Zwolle'.Versiebeheer (3D-Viewer Instant App):20230919 - Eerste gepubliceerde versie van dit item.