Interactive globe requires WebGL support.
Featured Articles
Deep dives into the technologies, architectures, and ideas shaping the future of geospatial intelligence.
Real-Time Spatial Streaming: Kafka, Flink, and Live Geofencing
Batch spatial tooling breaks down on moving objects. How to build a streaming geofence pipeline with Redpanda and Apache Flink, using H3 cell IDs as the partition key so containment becomes a hash lookup rather than a geometry test.
Analytics & IntelligenceRouting and Isochrones on Open Data: pgRouting, OSRM, and Valhalla
Commercial routing APIs charge per element for something you can self-host on a $20 VPS. A decision framework across pgRouting, OSRM, Valhalla, and GraphHopper, with a 10,000 × 10,000 matrix benchmark and honest notes on where paid traffic data still wins.
Tools & TechnologyLiDAR and Point Clouds at Scale: PDAL, COPC, and Web Delivery
National LiDAR programmes are the largest open geospatial datasets in existence, and almost nobody uses them well. A practical guide to PDAL pipelines, ground classification, COPC, and streaming billions of points to a browser without a tile server.
Compute & InfrastructureSpatial Processing on HPC: From Your Laptop to a Thousand Cores
High Performance Computing for geospatial work, written for people who have an allocation and no idea what to do with it. What a cluster is, why it makes your job slower, how storage tiers change every rule, and a Python workflow taken from serial script to Slurm job array to multi-node MPI.
ArchitectureBuilding a Geospatial Digital Twin: Imagery, Processing, and Live Data
A complete digital twin built from open source components only — drone photogrammetry with OpenDroneMap, LiDAR classification with PDAL, 3D Tiles and COPC delivery, and live sensor binding via MQTT and SensorThings. With real costs and honest limitations.
Python PerformancecuSpatial: GPU-Accelerated Spatial Analytics with RAPIDS
cuSpatial brings GPU acceleration to spatial operations — point-in-polygon, nearest-neighbour, trajectory analysis, and more — via the RAPIDS ecosystem. When CPU-based tools hit their ceiling on very large datasets, cuSpatial can deliver 10–100x additional speedups.
Key Themes
Built for Practitioners, Architects, and Curious Minds
GeoIntelligence.io is an independent publication covering the intersection of spatial data, modern software architecture, and applied intelligence. We write for engineers transitioning from monolithic GIS, architects designing cloud-native spatial systems, and analysts who want to derive real meaning from location data.
Learn More About Us →