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GIS as a BIM substrate

Building Information Modelling (BIM) occupies the building scale: structural geometry, material assemblies, mechanical systems, occupancy. A model is meaningful in isolation, but its commercial value emerges when it is sited — positioned in a real geography with real neighbours, real catchments, and real regulatory context. The PointSav GIS co-location dataset is designed to provide that siting context to BIM composition pipelines.

This article documents what the GIS dataset offers a BIM consumer, which fields are stable, and what extensions are anticipated.

The cluster manifold

The primary GIS output is a manifold of approximately 6,400 deduplicated commercial co-location clusters across the United States, Canada, Mexico, the United Kingdom, and continental Europe. Each cluster carries:

  • a stable identifier and fixed geographic position (latitude/longitude)
  • the regional name resolved through the layered boundary engine
  • the tier classification (Regional, District, Local, Fringe)
  • the categorical composition (which anchor types are present)
  • the count of stores within nested catchment radii (1 km, 2 km, 3 km)

For a BIM consumer, this manifold answers questions a model alone cannot: How densely commercial is the area within 3 km of this proposed building? Which anchor formats already serve the catchment? Where is the nearest equivalent existing site against which a model could be benchmarked?

Cluster properties available for BIM ingest

Each cluster's properties record carries fields suitable for direct ingest by a city-code composition pipeline:

Field Type BIM use
cluster_id string Stable join key
latitude, longitude, centroid_lat, centroid_lon float Anchor and centroid positions for siting
region_name string Resolved metro or municipal name; useful as a model parameter
tier_descriptor string Regional / District / Local / Fringe — density signal
count_1km, count_3km integer Catchment density
unique_brands integer Distinct retail brands within catchment
merged_zones array Same-zone clusters consolidated; shown for transparency
iso, state string Jurisdiction codes

The cluster manifold is published as PMTiles with a layer schema supporting individual store positions (Layer 1) and cluster envelopes with proximity rings (Layer 2). A BIM consumer can fetch the GeoJSON manifest at /data/clusters-meta.json for direct lat/lon access, or read the PMTiles directly via byte-range requests for spatially indexed queries.

Region resolution depth

The boundary engine resolves coordinates to one of five granularities, from most specific to most general:

  1. GADM admin-3 (Canadian Census Subdivision proxies, Mexican Municipios)
  2. GADM admin-2 (where admin-3 is unavailable)
  3. Eurostat NUTS-3 (European regions)
  4. Statistics Canada CMA / US Census Core-Based Statistical Area
  5. Natural Earth admin-1 (state/province global fallback)

A BIM composition that needs to anchor against a municipal jurisdiction — for instance, a building proposed inside Strathcona County in Alberta — receives that level of resolution. A composition that needs only a metropolitan reference frame receives the surrounding CMA.

Civic context layers

Beyond the cluster manifold, the GIS dataset includes two civic layers relevant to building programmes that depend on civic adjacency:

  • Hospital catalogue. Approximately 28,000 hospital locations across the operational footprint, sourced from OpenStreetMap.
  • University catalogue. Approximately 19,000 higher-education locations, similarly sourced.

Distance to the nearest hospital and nearest university are computed per cluster within a 5 km practical limit. For a BIM consumer modelling a healthcare-adjacent or campus-adjacent programme, these distances are direct inputs.

Stability guarantees

Stable across releases: cluster identifiers, the manifold structure, the tier classification scheme, the regional name resolution algorithm, and the catchment radii.

Likely to change: the size of the brand-family taxonomy (food and pharmacy families are expanding), the absolute store counts (OpenStreetMap coverage is improving year over year), and the inclusion of additional countries (Belgium, Luxembourg, Ireland, and Switzerland are absent from the May 2026 footprint).

A BIM composition that joins on cluster_id sees growth but no deletion of existing identifiers. A composition that joins on region_name should be aware that text values may shift slightly with each region-engine refinement.

See Also

References

Important Information

Important Information

Securities offering. Woodfine Capital Projects Inc. ("Woodfine") sponsors real-property direct-hold solutions. Interests in those solutions are offered only to investors who qualify under an applicable prospectus exemption — including the accredited-investor exemption under National Instrument 45-106 — Prospectus Exemptions, and equivalent exemptions in other applicable jurisdictions. Content on this wiki is provided for general informational purposes only and does not constitute an offer to sell, or a solicitation of an offer to buy, any security. Any offering is made exclusively by means of the applicable Private Placement Memorandum, which prospective investors should review, together with their own professional advisors, before investing.

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Risk. Investment in real-property direct-hold solutions involves significant risk, including possible loss of capital. Past performance is not indicative of future results. References to structural features such as advisory fees, transferability, and net asset value methodology describe the contractual terms of the direct-hold solutions and are not representations as to investment outcomes or returns.

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