Introduction ¶

The piece discusses implementing zonal operations techniques using cloud storage and PostGIS database systems. The author references training materials from the QGIS Changelog site, specifically a lesson on “Zonal Operations,” and demonstrates how to replicate comparable results through cloud infrastructure and PostGIS.

Prerequisites ¶

The tutorial requires:

• Cloud storage solutions (MinIO, Amazon S3, or similar providers)
• PostgreSQL database instance
• ogr_fdw extension installed in PostgreSQL

Technical Setup ¶

The author provides a docker-compose configuration establishing:

• MinIO service for object storage (ports 9000, 9001)
• PostGIS 16 with version 3.4 (port 25432)
• Multiple extensions enabled: postgis, hstore, postgis_topology, postgis_raster, pgrouting, ogr_fdw

Implementation Steps ¶

The workflow includes:

1. Launching services via docker-compose
2. Creating MinIO bucket and uploading sample datasets
3. Installing postgis tools within the container
4. Loading raster data using raster2pgsql command
5. Accessing spatial data via GDAL and GDAL’s /vsicurl protocol
6. Creating remote servers and foreign tables using ogr_fdw
7. Generating materialized views for performance optimization
8. Executing SQL queries for generating zonal statistics

Key SQL Operations ¶

The author demonstrates creating remote data connections and executing summary statistics queries on clipped raster data by district boundaries.

Conclusion ¶

The piece emphasizes that “multiple ways” exist for addressing geospatial challenges, with cloud storage enabling diverse tools to access identical datasets for various analytical purposes.