VECTORIO“The data is free; the pipeline from scene to decision is not”
Satellite scenes to a signed city map.
Reproducible, citable planning map from raw scenes
- The data is free, but turning gigabyte scenes into a planner's map is the hard part.
- I stitched five tools together and cannot re-run it when the data updates.
- The city must show this is the calculation we made, on these inputs.
- Reproducible, citable planning map from raw scenes
- Same input yields the same aggregate even with flaky sources
- No cloud dependency for municipal geodata
From today to the first result.
five tools stitched together
The chain from scene to map cannot be rerun when the data updates, and live feeds arrive paginated, late and duplicated.
One 30-node workflow from GDAL ingest to signed GeoJSON reruns on every data update, with rolling windows that give the same aggregate each time.
Rebuild one map product as a workflow and keep your existing tools alongside.
one mapVegetation index from satellite bands. Step by step.
Red and near-infrared bands are joined per pixel and turned into a vegetation index report.
- Red Band · NIR BandRandomDataProvider · RandomDataProvider
- Join R + NIR BandsHash Join
- Compute NDVICompute Fields
- NDVI Report CSVCSV Publisher
band-r → Generators.Random
band-nir → Generators.Random
band-join → ETL.HashJoin
ndvi-compute → ETL.Compute
ndvi-csv → CSV.Publisher- Red BandSupplies 10,000 red-band pixel values.
- Join R + NIR BandsWaits for the NIR band, then inner-joins both bands on pixel id.
- Compute NDVICalculates NDVI per pixel.
- NDVI Report CSVWrites the NDVI report.
A real workflow from our end-to-end test suite; the designer view is illustrated.
What you get. From the first pilot.
Reproducible, citable planning map from raw scenes
Same input yields the same aggregate even with flaky sources
No cloud dependency for municipal geodata
Why your tools fall short.
ArcGIS and QGIS are built for interactive work
Google Earth Engine / cloud EO platforms conflict with data sovereignty and lock in
Python+GDAL scripts break and carry no audit trail
- Heat and climate adaptation obligations for cities
- Free Copernicus data lowering entry barrier
- Municipal desire for sovereign tooling
Your pilot. Three steps.
Your data shape
Tell us what data you have, where it lives and what the result must be.
A scoped pilot
On your data and your hardware, with the success measure written down first.
A clear decision
You see the result against that measure — and keep every workflow and record.
Related roles in Research & geodata.
Bring us your hardest data problem. Let's solve it together.
A short pilot on your data and your hardware. We agree on what success looks like before we start.