Data overview — location intelligence and GIS data layers
The PointSav platform produces and serves geospatial data in two primary forms: a location intelligence cluster dataset covering commercial co-location patterns across multiple countries, and a point-of-interest taxonomy that underlies the cluster algorithm. This article orients readers to those layers and links to the substantive methodology and archetype articles.
Location intelligence clusters
The cluster dataset groups commercial points of interest into co-location nodes — this article uses a three-tier T1 (anchor) / T2 (developed) / T3 (emerging) vocabulary — using a two-pass DBSCAN algorithm. This tier vocabulary has not been reconciled against the tier naming used elsewhere on this wiki (see Nordic and UK coverage expansion and related articles); a reader comparing tier labels across articles should treat the naming here as this article's own, not yet a single canonical system. Three archetypes describe distinct commercial patterns: PRO (professional retail co-location), VWH (Urban Fringe — urban logistics and light-manufacturing clusters with no hypermarket anchor), and PKS (parking structures / transit-adjacent commercial).
See Location Intelligence Co-location Archetypes for a full introduction.
GIS tile pipeline
Cluster data is compiled into PMTiles and served at gis.woodfinegroup.com. The pipeline runs nightly, producing updated archetype GeoJSON files and spatial tile layers. See the Developer Guide Catalog for the nightly rebuild and AEC hazard pipeline guides.
Methodology articles
- O-D Catchment Methodology — crow-flies origin-destination model and catchment ring rationale
- Catchment Ranking Methodology — combined primary and secondary rank dimensions
- Co-location Tier Nomenclature — T1/T2/T3 vocabulary
This article is a stub. Full content is planned for a future session.