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Dutch Planners: 6 Step Public Space Modelling Using 3DBAG and AHN

Anne Dullemond

— 8 min read
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Dutch Planners: 6 Step Public Space Modelling Using 3DBAG and AHN

The most effective way to model public space is a short, repeatable workflow: collect authoritative data, build the geometry, run the priority analyses, visualise the results and consult stakeholders. National datasets such as the 3D Basisvoorziening and 3DBAG, combined with the IMBOR informatiemodel, give the model a shared, verifiable foundation. Priority analyses cover pedestrian flows, sunlight and shadow, and visibility. A browser-based platform can run this entire sequence without local installation.

TL;DR:Using authoritative Dutch datasets like 3D Basisvoorziening and 3DBAG ensures models are verifiable and suitable for analyses such as pedestrian flow, shadow, and visibility.Defining clear scope and success criteria before data collection and analysis prevents rework caused by choosing incorrect Level of Detail or scope.Running shadow and visibility analyses together during the same geometry pass improves efficiency and result comparability, saving time and effort.Light versions of models (LoD1.2 or similar) usually suffice for early feasibility, while detailed designs should employ higher levels of detail and specific analyses.Browser-based platforms like 3D Cityplanner facilitate the entire workflow, from data ingestion to scenario comparison, without local software installation.

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Table of Contents

Practical step-by-step workflow for modelling public space

A public-space model earns its value only when it answers a specific planning question, so the first task is defining what that question is and at what scale. A feasibility study for a neighbourhood square needs a different level of detail than a detailed design for a single street. Fix the scope, the geographic extent and the criteria for success before opening any software.

  1. Define scope and success criteria. Decide what decision the model must support, at what scale and by which date, and write down the analyses that will answer it.
  2. Collect and pre-process base data. Pull BAG for building identifiers, BGT for topography, AHN for elevation, 3DBAG for building geometry and the relevant PDOK collections for terrain and context.
  3. Build or import geometry. Import the base datasets, set the level of detail (LoD) each analysis needs and attach an attribute schema that matches later reporting requirements.
  4. Run the priority analyses. Test pedestrian flows, shading, visibility, drainage screening and, where relevant, noise screening, using the geometry and attributes prepared in the previous step.
  5. Produce visualisations and public-facing materials. Translate analysis outputs into renderings, annotated plans and interactive views that non-technical stakeholders can read without training.
  6. Version and compare scenarios. Keep each design option as a separate, comparable scenario so decision-makers can weigh trade-offs side by side rather than in the abstract.

Each step produces a deliverable that the next step depends on, which is what makes the sequence repeatable across projects rather than a one-off exercise. Skipping the scoping step is the most common cause of rework, because teams often discover halfway through modelling that the wrong LoD was chosen for the analysis they actually need. A worked example: a municipality assessing a 4,000 square metre market square would scope for pedestrian-flow and shading analysis, import 3DBAG massing at LoD1.2 for surrounding buildings, run shadow checks against the equinox and midsummer sun angles, and produce two scenarios: one with a central pavilion, one without. The comparison, not the geometry itself, is the deliverable that goes to the council.

For teams building this sequence for the first time, a structured 3D building modelling tutorial or a guide to creating 3D city models can shorten the learning curve considerably.

Six-stage public-space modelling workflow

Which analyses to run and when

Not every project needs every analysis, and running a heavy simulation on a light-touch project wastes budget without improving the decision.

  • Pedestrian-flow modelling needs origin and destination points and accurate walkway geometry as inputs, and produces density maps and pinch-point locations as outputs; commission detailed agent-based simulation only when a square or station forecourt has genuinely complex, overlapping movement patterns.
  • Sun and shadow analysis should test seasonal envelopes, typically equinox and midsummer, against fixed receptor points such as terraces or playgrounds, and the output should identify both the problem hours and a mitigation option, such as building height or canopy placement.
  • Visibility and sightline checks verify that sightlines across a square or junction meet safety expectations and that key landmarks remain visible from approach routes, which matters as much for placemaking as for security.
  • Noise and drainage screening is usually sufficient at a coarse level for early feasibility, using existing BGT and AHN data, but detailed acoustic or hydrological modelling becomes necessary once a scheme approaches formal permitting.

Pro Tip: Run shadow and visibility checks on the same geometry pass rather than rebuilding the model for each analysis: it saves time and keeps the results directly comparable.

The academic literature on data-driven public-space planning argues for treating public space as a multifunctional network rather than leftover land between buildings, which is precisely why running several lighter analyses together, instead of one deep analysis in isolation, tends to produce a more balanced design.

File formats, interoperability and practical integration tips

Choosing the right file format early avoids the painful step of re-exporting a model halfway through a project because a viewer or consultant cannot open it.

  • CityJSON is compact, human-readable and well suited to analysis workflows that need to query building attributes alongside geometry.
  • IFC remains the standard for detailed architectural and infrastructure elements, useful once a public-space scheme includes structures designed in BIM software.
  • CityGML carries rich semantic structure and is often used for exchange between government systems, though it is heavier to handle than CityJSON for quick iteration.
  • 3D Tiles is built for streaming large-scale terrain and building datasets into web viewers, which makes it the practical choice for the visualisation stage rather than for analysis.

Level of detail should follow the analysis, not the other way round: a shadow study can often run on LoD1.2 massing, while a visibility check at street level may need LoD2 facade detail. Keep original geometry alongside any simplified version so it can be reused at a later project stage rather than rebuilt. Linking every object to its BAG or 3DBAG identifier, and tagging it with the matching IMBOR code where relevant, preserves provenance and makes it possible to trace a modelled object back to its authoritative source months later. For export, a lighter 3D Tiles or CityJSON package tends to load faster in browser-based viewers than a full CityGML dataset, which matters when the deliverable is a stakeholder-facing interactive view rather than an internal analysis file.

Visualisation and stakeholder engagement: outputs that win approvals

Analysis results only change decisions when the people making them can read the results without a technical briefing.

  1. Prepare a mix of static renderings, annotated plans and an interactive viewer, since different stakeholders absorb information differently and a single format rarely serves a full council chamber and a residents’ evening equally well.
  2. Structure the participation session around scenario comparisons, showing two or three design options side by side with simple KPI summaries rather than a single polished image that invites a yes or no answer.
  3. Check that every visual reflects the underlying analysis, cross-referencing shadow times and pedestrian hotspots against the rendering before it goes public, so the image never promises more than the data supports.

Practitioners working with 3D and VR visualisation report that it helps both technical checks and stakeholder engagement, because it lets residents give more specific feedback earlier in the process than a 2D plan typically allows. That earlier feedback tends to reduce costly late-stage redesigns.

Using 3D Cityplanner in an openbare ruimte workflow

This type of platform can ingest PDOK, 3DBAG and AHN data directly and generate a working site overview in a browser, without local installation or file conversion.

  • Out-of-the-box analyses cover sunlight and shadow, visibility, parking and development capacity, which speeds up the early feasibility checks described earlier in this workflow.
  • Scenario duplication lets a planner copy a baseline model and adjust massing, greenery or paving in a second version without rebuilding the geometry.
  • Export paths support sharing scenarios as interactive views for stakeholder sessions, matching the visualisation step covered above.

New projects typically start by linking the relevant PDOK and 3DBAG datasets, then duplicating the base scenario for each design option under review. The digital twin platform is built around exactly this scenario-comparison logic.

When to model in 3D and when lighter approaches suffice

Model fidelity should track project stage, not enthusiasm for detail. Strategic-level plans need only massing and a coarse shadow or capacity check; feasibility studies justify LoD2 geometry and the core analyses covered above; detailed design stages, where planting, drainage and paving specifications matter, often call for a specialist consultant. Keep early massing models rather than discarding them, since they save real rework once a project moves to the next stage.

— Anne Dullemond

How 3D Cityplanner can help with your next public-space project

Some browser-based platforms run the full workflow above: national data ingestion, scenario comparison and sun, visibility and capacity analyses that a feasibility study needs, without local software installation.

For a turnkey study, the Gebiedsscan service delivers a rapid site analysis without setting up the platform yourself. Readers ready to test the workflow on a live project can view pricing and plans or request a demo directly.

Sources

Public-space models are only as trustworthy as the data underneath them, and the Netherlands has an unusually complete set of open, authoritative sources to draw on.

Mapping IMBOR attributes into a 3D model early, rather than retrofitting them later, keeps the model useful beyond the design phase because maintenance teams and procurement processes can read the same object definitions. Update schedules vary by collection: 3DBAG refreshes as BAG mutations are processed, while some 3D Basisvoorziening collections update on a slower cycle, so it is worth checking currency before locking a baseline. Licensing across PDOK and Kadaster products is generally open, but always confirm the specific collection’s terms before redistributing derived models to third parties.

FAQ

What is the best workflow to model public space?

The most reliable sequence is data collection, geometry building, analysis, visualisation and stakeholder consultation, repeated as scenarios are compared. Using authoritative Dutch datasets such as the 3D Basisvoorziening and 3DBAG at the start keeps every later step traceable.

Which Dutch datasets are essential for 3D public-space models?

The core set is BAG, BGT, AHN, 3DBAG and the relevant 3D Basisvoorziening collections accessed through PDOK. These together supply building geometry, topography and elevation for most feasibility-level models.

What is IMBOR and why does it matter for modelling?

IMBOR is the Dutch informatiemodel for public-space assets, standardising how objects like street furniture and greenery are classified and described. Mapping model attributes to IMBOR codes keeps a design model useful for later asset management and procurement.

Which analyses should every public-space model include?

Pedestrian-flow, sun and shadow, and visibility analyses cover most early planning questions and can usually run on the same base geometry. Noise and drainage screening are added once a scheme moves toward formal permitting.

Can 3D Cityplanner handle this entire workflow?

3D Cityplanner ingests PDOK, 3DBAG and AHN data directly and includes built-in sun, visibility, parking and capacity analyses, covering most of the workflow described here in a browser. Pricing starts at €79 per month for the Starter plan.

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