Geospatial

Geospatial workflows are needed when visual data must stay connected to real-world coordinates. Typical tasks include mapping infrastructure, monitoring land and vegetation, extracting road and building features, and preparing training data for location-aware AI systems.

We include this industry section in Use Cases to show how Supervisely solves practical geospatial problems end to end, not just isolated annotation tasks.

When Geospatial Workflows Are Needed

Teams usually need geospatial workflows when they work with:

• Satellite or aerial imagery.

• Elevation layers such as DTM/DEM.

• Coordinate-aware vector data like OpenStreetMap features.

• Projects where annotations must be exported back to geodata formats.

How Supervisely Helps

Supervisely provides a unified pipeline for geospatial computer vision:

• Data acquisition with ecosystem apps that can fetch satellite imagery, terrain data, and OSM features.

• Multi-layer annotation with interfaces such as Multiview and Overlay for side-by-side or blended inspection.

• AI-assisted labeling with Smart Tool and model-assisted workflows to speed up annotation.

• Team collaboration and quality control using labeling jobs, reviews, and performance tracking.

• Export to geodata with conversion back to OSM-compatible formats.

This approach allows teams to keep one consistent workflow from data collection to model-ready output.

Start Here

• Geospatial Data Annotation - detailed step-by-step workflow in Supervisely.

• Geospatial Images in Python SDK - corresponding Developer Portal tutorial for programmatic workflows.