Geospatial Data Pipeline

This handles the full stack of geospatial work: processing drone imagery, transforming coordinate systems, generating map tiles, and running spatial queries at scale. Built around PostGIS and GDAL, it steers you away from common mistakes like storing coordinates as strings, skipping spatial indexes, or loading 50MB GeoJSON files directly into the browser. The anti-pattern examples are especially useful if you've hit performance walls with proximity queries or mixed up WGS84 and Web Mercator projections. Best for mapping apps and location services where you need real spatial analysis, not just basic distance calculations or address lookups.

skills.sh installs: 197
GitHub stars: 113
last updated: Jun 3, 2026

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Install

$ npx -y skills add erichowens/some_claude_skills --skill geospatial-data-pipeline --agent claude-code

Installs into .claude/skills of the current project.

Files

Geospatial Data Pipeline

Expert in processing, optimizing, and visualizing geospatial data at scale.

When to Use

✅ Use for:

Drone imagery processing and annotation
GPS track analysis and visualization
Location-based search (find nearby X)
Map tile generation for web/mobile
Coordinate system transformations
Geofencing and spatial queries
GeoJSON optimization for web

❌ NOT for:

Simple address validation (use address APIs)
Basic distance calculations (use Haversine formula)
Static map embeds (use Mapbox Static API)
Geocoding (use Nominatim or Google Geocoding API)

Technology Selection

Database: PostGIS vs MongoDB Geospatial

Feature	PostGIS	MongoDB
Spatial indexes	GiST, SP-GiST	2dsphere
Query language	SQL + spatial functions	Aggregation pipeline
Geometry types	20+ (full OGC support)	Basic (Point, Line, Polygon)
Coordinate systems	6000+ via EPSG	WGS84 only
Performance (10M points)	<100ms	<200ms
Best for	Complex spatial analysis	Document-centric apps