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--- ---
schema: foundry-doc-v1 schema: foundry-doc-v1
title: "Places filtering service" title: "Places filtering service"
slug: service-places-filtering slug: service-places-filtering
category: services category: services
type: topic type: topic
quality: complete quality: complete
status: active status: active
audience: public audience: public
short_description: "service-places filters raw civic and institutional infrastructure data to retain only regional-grade facilities — hospitals, universities, and major transport hubs — so GIS tier rankings reflect institutional-level concentration rather than local-service density." short_description: "service-places filters raw civic and institutional infrastructure data to retain only regional-grade facilities — hospitals, universities, and major transport hubs — so GIS tier rankings reflect institutional-level concentration rather than local-service density."
bcsc_class: public-disclosure-safe bcsc_class: public-disclosure-safe
language_protocol: PROSE-TOPIC language_protocol: PROSE-TOPIC
last_edited: 2026-05-08 last_edited: 2026-05-08
editor: pointsav-engineering editor: pointsav-engineering
paired_with: service-places-filtering.es.md paired_with: service-places-filtering.es.md
cites: [] cites: []
--- ---
[[co-location-methodology|GIS tier rankings]] depend on knowing where regional institutions sit, not where every clinic and community college sits. **`service-places`** filters raw civic data to retain only regional-grade facilities — hospitals with at least 50 staffed beds, universities with at least 1,000 full-time-equivalent students, validated major regional transport hubs — and applies a 200 m spatial buffer to consolidate large institutional campuses into single regional anchors. Local-service density is filtered out at this stage; downstream rankings reflect institutional concentration rather than facility count. [[co-location-methodology|GIS tier rankings]] depend on knowing where regional institutions sit, not where every clinic and community college sits. **`service-places`** filters raw civic data to retain only regional-grade facilities — hospitals with at least 50 staffed beds, universities with at least 1,000 full-time-equivalent students, validated major regional transport hubs — and applies a 200 m spatial buffer to consolidate large institutional campuses into single regional anchors. Local-service density is filtered out at this stage; downstream rankings reflect institutional concentration rather than facility count.
## Filtering Thresholds ## Filtering Thresholds
The service applies attribute-weight filters to the raw civic data provided by [[service-fs-data-lake|`service-fs`]]: The service applies attribute-weight filters to the raw civic data provided by [[service-fs-data-lake|`service-fs`]]:
- **Regional hospitals:** minimum capacity threshold (50+ staffed beds). - **Regional hospitals:** minimum capacity threshold (50+ staffed beds).
- **Regional universities:** minimum enrollment threshold (1,000+ full-time equivalent students). - **Regional universities:** minimum enrollment threshold (1,000+ full-time equivalent students).
- **Airports:** validated as major regional transport hubs; general aviation facilities are excluded. - **Airports:** validated as major regional transport hubs; general aviation facilities are excluded.
## Spatial Aggregation ## Spatial Aggregation
Large institutional campuses frequently appear in raw open geospatial data as multiple separate points. `service-places` applies a 200 m spatial buffer to cluster these into a single regional anchor with a unified center of gravity, preventing over-counting of large campus footprints. Large institutional campuses frequently appear in raw open geospatial data as multiple separate points. `service-places` applies a 200 m spatial buffer to cluster these into a single regional anchor with a unified center of gravity, preventing over-counting of large campus footprints.
## Data Output ## Data Output
The resulting `cleansed-places.jsonl` provides the regional anchor dataset that [[app-orchestration-gis]] uses when awarding final [[co-location-methodology|co-location tier rankings]]. The resulting `cleansed-places.jsonl` provides the regional anchor dataset that [[app-orchestration-gis]] uses when awarding final [[co-location-methodology|co-location tier rankings]].
## See also ## See also
- [[service-fs-data-lake]] — GIS data lake supplying the raw civic and retail data - [[service-fs-data-lake]] — GIS data lake supplying the raw civic and retail data
- [[service-business-clustering]] — retail clustering service that consumes the filtered place data - [[service-business-clustering]] — retail clustering service that consumes the filtered place data
- [[app-orchestration-gis]] — orchestration layer that assembles tier rankings from both services - [[app-orchestration-gis]] — orchestration layer that assembles tier rankings from both services
- [[co-location-methodology]] — the ranking methodology driving tier assignments - [[co-location-methodology]] — the ranking methodology driving tier assignments