PostGIS 3.6.1 Spatial Database
Overview
PostGIS 3.6.1 (with GEOS 3.14) brings significant improvements: ST_CoverageClean for topology repair, enhanced SFCGAL 3D operations, bigint topology support for massive datasets, and improved PostgreSQL 18 integration. This skill ensures you leverage these capabilities correctly.
Core principle: Spatial is special. Generic database patterns often fail with geographic data.
Announce at start: "I'm applying postgis to ensure PostGIS 3.6.1 spatial best practices."
When This Skill Applies
This skill is MANDATORY when ANY of these patterns are touched:
| Pattern | Examples |
|---|---|
**/*geo* | models/geography.ts, geo_utils.py |
**/*spatial* | lib/spatial.ts |
**/*location* | services/locationService.ts |
**/*coordinate* | types/coordinates.ts |
**/*polygon* | db/polygons.sql |
**/*geometry* | migrations/add_geometry.sql |
**/*postgis* | setup/postgis.sql |
**/*gis* | utils/gis.ts |
Or when files contain:
-- These patterns trigger this skill ST_* geography geometry SRID
PostGIS 3.6.1 Features
1. ST_CoverageClean (New in 3.6.1)
Coverage cleaning repairs topological errors in polygon collections. Requires GEOS 3.14:
-- Clean a set of polygons that should form a seamless coverage -- Fixes: overlaps, gaps, edge inconsistencies SELECT ST_CoverageClean( ARRAY[polygon1, polygon2, polygon3]::geometry[] ) AS cleaned_polygons; -- Use case: Administrative boundaries, parcels, zones -- Before: Manual repair with ST_MakeValid, ST_SnapToGrid -- After: Single function handles entire coverage -- Example: Clean municipal boundaries WITH boundaries AS ( SELECT geom FROM municipalities ) SELECT ST_CoverageClean(array_agg(geom)) FROM boundaries;
When to use:
- •Importing GIS data with topological errors
- •Merging datasets from different sources
- •Ensuring seamless coverage (no gaps/overlaps)
- •Cadastral/parcel data management
2. SFCGAL 3D Functions
PostGIS 3.6.1 includes enhanced SFCGAL support for 3D operations:
-- Enable SFCGAL (if not already enabled)
CREATE EXTENSION IF NOT EXISTS postgis_sfcgal;
-- 3D intersection (true 3D, not projection)
SELECT ST_3DIntersection(
ST_GeomFromText('POLYHEDRALSURFACE Z (...)'),
ST_GeomFromText('POLYHEDRALSURFACE Z (...)')
);
-- 3D union
SELECT ST_3DUnion(geom1, geom2);
-- 3D area (actual surface area in 3D)
SELECT ST_3DArea(polyhedral_surface);
-- Minkowski sum (for buffer-like operations in 3D)
SELECT ST_MinkowskiSum(geometry1, geometry2);
-- Straight skeleton (for building roofs, etc.)
SELECT ST_StraightSkeleton(polygon);
-- Extrude 2D to 3D
SELECT ST_Extrude(polygon, 0, 0, height);
Use cases:
- •Building/structure modeling
- •Underground infrastructure
- •Airspace management
- •3D terrain analysis
3. Bigint Topology Support
PostGIS 3.6.1 supports bigint topology IDs for massive datasets:
-- Create topology with bigint IDs (new in 3.6.1)
SELECT CreateTopology('massive_parcels', 4326, 0.0000001, true);
-- Last parameter: use_bigint = true
-- Supports > 2 billion features per topology
-- Previous limit: ~2 billion (int4 max)
-- Add layer
SELECT AddTopoGeometryColumn('massive_parcels', 'public', 'parcels', 'topogeom', 'POLYGON');
-- TopoGeometry operations work the same
SELECT ST_CreateTopoGeo('massive_parcels', geom);
When to use:
- •National/continental scale datasets
- •High-resolution parcel data
- •OpenStreetMap imports
- •Any topology > 2 billion edges
4. PostgreSQL 18 Interrupt Handling
PostGIS 3.6.1 properly handles PostgreSQL 18's improved query cancellation:
-- Long-running spatial operations can now be cancelled cleanly -- No more orphaned locks or corrupted state -- Example: Cancellable heavy operation SELECT ST_Union(geom) FROM very_large_table GROUP BY region; -- ^C now works properly -- COPY operations with PostGIS also respect cancellation COPY (SELECT id, ST_AsGeoJSON(geom) FROM features) TO '/tmp/export.json';
Data Types
Geometry vs Geography
-- GEOMETRY: Planar coordinates, any SRID -- Faster computations, less accurate over large distances CREATE TABLE places_geometry ( id uuid PRIMARY KEY DEFAULT uuidv7(), location geometry(Point, 4326) -- WGS84 ); -- GEOGRAPHY: Spherical coordinates, always WGS84 -- Accurate distances/areas, slower computations CREATE TABLE places_geography ( id uuid PRIMARY KEY DEFAULT uuidv7(), location geography(Point, 4326) -- Always WGS84 ); -- When to use GEOMETRY: -- - Local/city-scale applications -- - Need complex operations (union, intersection) -- - Performance critical -- - Non-earth data (game maps, floor plans) -- When to use GEOGRAPHY: -- - Global applications -- - Distance/area accuracy matters -- - Simple operations (distance, contains) -- - User-facing distance calculations
Choosing SRID
-- Common SRIDs: -- 4326: WGS84 (GPS coordinates, web maps) -- 3857: Web Mercator (tile-based web maps, display only) -- Local projections for accurate measurements -- ALWAYS store in 4326 (WGS84) as source of truth -- Transform for calculations when needed CREATE TABLE locations ( id uuid PRIMARY KEY DEFAULT uuidv7(), name text NOT NULL, location geography(Point, 4326), -- Storage location_local geometry(Point) -- NULL, computed as needed ); -- Transform for local calculations SELECT ST_Transform( location::geometry, 32610 -- UTM Zone 10N (California) ) FROM locations WHERE name = 'San Francisco';
Index Strategy
Spatial Indexes
-- GiST index: Default for most spatial queries CREATE INDEX idx_locations_geom ON locations USING gist(location); -- BRIN index: For very large, naturally ordered datasets -- (e.g., GPS tracks ordered by time) CREATE INDEX idx_tracks_geom ON gps_tracks USING brin(location); -- SP-GiST: For non-overlapping data (points, IP ranges) CREATE INDEX idx_points_spgist ON points USING spgist(location);
Index Best Practices
-- Always include spatial index CREATE TABLE features ( id uuid PRIMARY KEY DEFAULT uuidv7(), geom geometry(Polygon, 4326), created_at timestamptz DEFAULT now() ); CREATE INDEX idx_features_geom ON features USING gist(geom); -- Partial spatial index for active records CREATE INDEX idx_features_geom_active ON features USING gist(geom) WHERE deleted_at IS NULL; -- Composite index for common query patterns CREATE INDEX idx_features_type_geom ON features USING gist(geom) WHERE feature_type = 'building';
Index Clustering
-- Cluster table by spatial index for range query performance CLUSTER features USING idx_features_geom; -- For large tables, recluster periodically -- Schedule during maintenance window
Query Patterns
Distance Queries
-- Find points within distance (geography, in meters) SELECT * FROM locations WHERE ST_DWithin( location, ST_MakePoint(-122.4194, 37.7749)::geography, 1000 -- 1km radius ); -- Find points within distance (geometry, in SRID units) SELECT * FROM locations WHERE ST_DWithin( location, ST_SetSRID(ST_MakePoint(-122.4194, 37.7749), 4326), 0.01 -- ~1km at this latitude (degrees) ); -- K-nearest neighbors (KNN) SELECT *, location <-> ST_MakePoint(-122.4194, 37.7749)::geography AS distance FROM locations ORDER BY location <-> ST_MakePoint(-122.4194, 37.7749)::geography LIMIT 10; -- Uses index for efficient KNN
Containment Queries
-- Points within polygon SELECT * FROM points WHERE ST_Within(location, ( SELECT boundary FROM regions WHERE name = 'California' )); -- Polygon contains point SELECT * FROM regions WHERE ST_Contains(boundary, ST_MakePoint(-122.4194, 37.7749)); -- Intersects (overlaps in any way) SELECT * FROM features WHERE ST_Intersects(geom, query_polygon);
Aggregation
-- Union all geometries SELECT ST_Union(geom) FROM parcels WHERE owner = 'City'; -- Collect without merging (faster, preserves individual geometries) SELECT ST_Collect(geom) FROM parcels WHERE owner = 'City'; -- Extent (bounding box) SELECT ST_Extent(geom) FROM features; -- Centroid of all points SELECT ST_Centroid(ST_Collect(location)) FROM locations;
GeoJSON Integration
Import/Export
-- Geometry to GeoJSON
SELECT ST_AsGeoJSON(location) FROM locations WHERE id = $1;
-- Geometry with properties to Feature
SELECT jsonb_build_object(
'type', 'Feature',
'geometry', ST_AsGeoJSON(location)::jsonb,
'properties', jsonb_build_object(
'id', id,
'name', name
)
) FROM locations WHERE id = $1;
-- FeatureCollection
SELECT jsonb_build_object(
'type', 'FeatureCollection',
'features', jsonb_agg(
jsonb_build_object(
'type', 'Feature',
'geometry', ST_AsGeoJSON(location)::jsonb,
'properties', jsonb_build_object('id', id, 'name', name)
)
)
) FROM locations;
-- GeoJSON to Geometry
INSERT INTO locations (name, location)
VALUES ('New Place', ST_GeomFromGeoJSON($1));
-- With SRID enforcement
INSERT INTO locations (name, location)
VALUES ('New Place', ST_SetSRID(ST_GeomFromGeoJSON($1), 4326));
API Response Pattern
-- Function for API endpoints
CREATE OR REPLACE FUNCTION get_locations_geojson(
bounds geometry DEFAULT NULL
)
RETURNS jsonb AS $$
SELECT jsonb_build_object(
'type', 'FeatureCollection',
'features', COALESCE(jsonb_agg(
jsonb_build_object(
'type', 'Feature',
'id', id,
'geometry', ST_AsGeoJSON(location, 6)::jsonb, -- 6 decimal places
'properties', jsonb_build_object(
'name', name,
'created_at', created_at
)
)
), '[]'::jsonb)
)
FROM locations
WHERE bounds IS NULL OR ST_Intersects(location::geometry, bounds);
$$ LANGUAGE sql STABLE;
Validation and Repair
Validate Geometries
-- Check validity SELECT id, ST_IsValid(geom), ST_IsValidReason(geom) FROM features WHERE NOT ST_IsValid(geom); -- Common issues: -- "Self-intersection" -- "Ring Self-intersection" -- "Too few points in geometry component" -- "Hole lies outside shell"
Repair Geometries
-- Simple repair (handles most issues) UPDATE features SET geom = ST_MakeValid(geom) WHERE NOT ST_IsValid(geom); -- Repair with specific strategy UPDATE features SET geom = ST_MakeValid(geom, 'method=structure') WHERE NOT ST_IsValid(geom); -- Coverage clean for polygon sets (3.6.1) WITH cleaned AS ( SELECT unnest(ST_CoverageClean(array_agg(geom ORDER BY id))) AS geom FROM parcels ) UPDATE parcels p SET geom = c.geom FROM cleaned c WHERE ST_Intersects(p.geom, c.geom); -- Snap to grid for precision issues UPDATE features SET geom = ST_SnapToGrid(geom, 0.000001) WHERE ST_NPoints(geom) > 1000; -- High-detail features
Performance Optimization
Query Optimization
-- Use && for bounding box pre-filter
SELECT * FROM features
WHERE geom && ST_MakeEnvelope(-122.5, 37.7, -122.4, 37.8, 4326)
AND ST_Intersects(geom, query_polygon);
-- Simplify for display (reduces transfer size)
SELECT id, ST_Simplify(geom, 0.0001) AS geom_display
FROM features;
-- Viewport-aware simplification
SELECT id,
CASE
WHEN zoom < 10 THEN ST_Simplify(geom, 0.01)
WHEN zoom < 14 THEN ST_Simplify(geom, 0.001)
ELSE geom
END AS geom
FROM features
WHERE geom && viewport_bounds;
Table Design for Spatial
-- Separate geometry from attributes for large tables
CREATE TABLE features (
id uuid PRIMARY KEY DEFAULT uuidv7(),
name text NOT NULL,
category text,
metadata jsonb DEFAULT '{}',
created_at timestamptz DEFAULT now()
);
CREATE TABLE feature_geometries (
feature_id uuid PRIMARY KEY REFERENCES features(id) ON DELETE CASCADE,
geom geometry(Geometry, 4326),
geom_simplified geometry(Geometry, 4326) -- Pre-computed simplification
);
CREATE INDEX idx_feature_geom ON feature_geometries USING gist(geom);
CREATE INDEX idx_feature_geom_simple ON feature_geometries USING gist(geom_simplified);
Materialized Views for Complex Queries
-- Pre-computed spatial joins CREATE MATERIALIZED VIEW feature_regions AS SELECT f.id AS feature_id, r.id AS region_id, r.name AS region_name FROM features f JOIN regions r ON ST_Within(f.location, r.boundary); CREATE UNIQUE INDEX idx_feature_regions ON feature_regions(feature_id); -- Refresh periodically REFRESH MATERIALIZED VIEW CONCURRENTLY feature_regions;
Migration Patterns
Adding Spatial Column
-- Step 1: Add column ALTER TABLE locations ADD COLUMN geom geometry(Point, 4326); -- Step 2: Create index CREATE INDEX CONCURRENTLY idx_locations_geom ON locations USING gist(geom); -- Step 3: Backfill from lat/lng UPDATE locations SET geom = ST_SetSRID(ST_MakePoint(longitude, latitude), 4326) WHERE geom IS NULL AND latitude IS NOT NULL; -- Step 4: Add constraint if needed ALTER TABLE locations ADD CONSTRAINT locations_geom_4326 CHECK (ST_SRID(geom) = 4326);
Converting Geometry to Geography
-- Create new column ALTER TABLE locations ADD COLUMN location_geo geography(Point, 4326); -- Migrate data UPDATE locations SET location_geo = location::geography WHERE location_geo IS NULL; -- Create index on new column CREATE INDEX CONCURRENTLY idx_locations_geo ON locations USING gist(location_geo); -- Update application, then drop old column ALTER TABLE locations DROP COLUMN location; ALTER TABLE locations RENAME COLUMN location_geo TO location;
PostGIS Artifact
When implementing spatial features, post this artifact:
<!-- POSTGIS_IMPLEMENTATION:START --> ## PostGIS Implementation Summary ### Spatial Columns | Table | Column | Type | SRID | Index | |-------|--------|------|------|-------| | locations | location | geography(Point) | 4326 | gist | | parcels | boundary | geometry(Polygon) | 4326 | gist | ### PostGIS 3.6.1 Features Used - [ ] ST_CoverageClean for topology repair - [ ] SFCGAL 3D functions - [ ] Bigint topology - [ ] PostgreSQL 18 interrupt handling ### Spatial Queries | Query Pattern | Index Used | Performance | |---------------|------------|-------------| | KNN distance | Yes (gist) | <10ms | | ST_Within region | Yes (gist) | <50ms | | ST_Intersects | Yes (gist) | <100ms | ### Validation - [ ] All geometries pass ST_IsValid - [ ] SRID constraints enforced - [ ] Spatial indexes created - [ ] Query patterns tested with EXPLAIN ANALYZE **PostGIS Version:** 3.6.1 **GEOS Version:** 3.14.x **Verified At:** [timestamp] <!-- POSTGIS_IMPLEMENTATION:END -->
Checklist
Before completing PostGIS implementation:
- • Correct data type chosen (geometry vs geography)
- • SRID is consistent (4326 recommended for storage)
- • Spatial indexes created on all geometry columns
- • Input geometries validated (ST_IsValid)
- • GeoJSON import/export tested
- • Query performance verified with EXPLAIN ANALYZE
- • PostGIS 3.6.1 features leveraged where appropriate
- • Artifact posted to issue
Integration
This skill integrates with:
- •
database-architecture- Spatial columns follow general schema patterns - •
postgres-rls- RLS policies can use spatial predicates - •
timescaledb- Time-series with spatial dimensions