GIS orchestration application
TopicFrom the PointSav Documentation
app-orchestration-gis is the stateless spatial analytics engine that performs linear-geometry calculations and coordinate mapping to produce the Woodfine co-location rankings and the interactive map at gis.woodfinegroup.com — a pure function that holds no canonical data and can be re-provisioned by pointing a fresh instance at the immutable data layer.
app-orchestration-gis is the stateless spatial analytics engine that performs linear-geometry calculations and coordinate mapping to produce the Woodfine co-location rankings and the interactive map at gis.woodfinegroup.com. The application holds no canonical data — it operates as a pure function from cleansed cluster files to ranked geo-tiles, so a lost instance can be re-provisioned by pointing a fresh process at the immutable Totebox data layer with no state migration. It runs on `os-orchestration` and composes with service-business-clustering and service-places-filtering to produce its input datasets.
[edit]Scoring Algorithm
The engine implements a linear geometric decay model using the Haversine formula. For every Alpha Anchor in the cleansed data layers, it calculates two proximity scores:
- Secondary proximity (3.0 km radius): score = max(0, 100 × (3.0 − distance_km) / 3.0)
- Tertiary proximity (5.0 km radius): score = max(0, 100 × (5.0 − distance_km) / 5.0)
The two scores combine to produce a continuous co-location score ranging from 0 to 400. Higher scores reflect greater convergence of capital-intensive operators within the defined catchment radii.
[edit]Tile Generation
The engine compiles scored output into vector tile assets for delivery to the interactive map:
- Vector tiles: PMTiles format for client-side rendering without a dedicated tile server [pmtiles-spec]
- Rendering: MapLibre GL JS processes the tiles client-side at high performance [maplibre-gl-js]
- Visual tiers: Spatial convergence across anchor categories (primary, hardware, warehouse, civic) maps to a four-tier visual classification on the map surface, expressed through the co-location scoring methodology
[edit]Stateless Architecture
The application holds no canonical data. It operates as a pure function: cleansed cluster files enter, ranked geo-tiles exit. If the application instance is lost, the entire analytics environment can be re-provisioned by pointing a fresh instance at the immutable data layer — no state migration required.
[edit]See also
- pointsav-gis-engine — the rendering layer that serves tiles produced by this engine
- service-business-clustering — the clustering service that groups POI data into co-location clusters
- service-places-filtering — the places filtering service that prepares cleansed input data
- co-location-methodology — the scoring and ranking methodology implemented by the engine
- location-intelligence-platform — the platform article covering the full GIS deployment
[edit]References
- Haversine formula — Wikipedia, accessed 2026-06-14