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Geospatial Data Pipelines & Automation

Can this run every week without us?

Your geospatial processing, automated: imagery, vectors and tables in, checked results out, on a schedule. Python GIS automation and spatial data management: ArcPy and GeoPandas scripts, PostGIS databases and Google Earth Engine pipelines that run without manual steps.

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We build scalable geospatial databases and automate repetitive GIS work. From automations and scripts to cloud processing, workflows inside web applications and back ends, and end-to-end pipelines, we make spatial data flow without manual effort.

That includes automated data pipelines, geospatial ETL, database design, monthly data-update systems, API integrations and cloud-based spatial processing — built on Python, ArcPy, GeoPandas, PostGIS, SQL and Google Earth Engine.

Distance to the high-voltage grid across Europe, mapped for data-centre siting

Who it is for

  1. Teams processing recurring satellite imagery
  2. Enterprises migrating to cloud-native GIS
  3. Organizations with complex multi-source data feeds
  4. Companies needing automated reporting pipelines

What we do.

Pipelines in Python, ArcPy, GeoPandas, PostGIS, SQL and Google Earth Engine, end to end.

  1. Automated ETL and ELT pipelines for spatial data.

A laptop showing code and a data pipeline diagram

ETL pipelines

Automated ETL and ELT pipelines for spatial data.

What you get.

What lands with your team at the end of the work. The bands play in turn; open any one.

Running

Data that moves itself

From source to map, without hands.

On a timer

Fresh every time

New data processed as it arrives.

Scales up

No laptop limits

Processing that grows with the data.

Checked

Know it is right

What was checked and what was fixed.

Connected

Talks to your systems

Your systems and the pipeline, linked.

Yours to run

One click

Tools your team runs without us.

How it is delivered.

What we need from you, what you receive, and what stays yours.

You give us

The area, the decision and the deadline, with your databases, feeds and legacy files.

We deliver

Automated ETL pipelinesScheduled processingCloud workflowsData quality reportsAPI integrationsPython toolboxes

Built with

Python, ArcPy, GeoPandas, PostGIS, SQL and Google Earth Engine.

You own it

The data, code and documentation are handed over, so your results never lock you into one vendor.

Need the results in an app? See Web GIS & Geospatial Apps.

Data we work with.

General kinds of data; which sources we use depends on the place and the question.

01

Google Earth Engine

Satellite archives, processed in the cloud.

02

Cloud storage

AWS and Azure.

03

Enterprise databases

The databases you already run.

04

Sensors and feeds

Streams that never stop.

05

Third-party APIs

Data from other services.

06

Legacy formats and CAD

Old files and drawings.

Where it is used.

The industries where this service is part of our work, and what we do in each.

Forest canopy seen from above Carbon, Forests & EnvironmentEarth Engine pipelines for land-cover time series Rows of crops across a field, with the sun low over the horizon Agriculture & Land ManagementSentinel-2 pipelines in Google Earth Engine A row of solar panels on grassland under a cloudy sky EnergyScreening pipelines that re-runCAD to GIS conversion A glass-roofed shopping arcade with shopfronts and shoppers Retail & Market IntelligenceAutomated territory and data pipelines Electricity pylons against an evening sky Infrastructure & UtilitiesCAD and legacy data conversion, georeferencing

Analyses that use it.

The types of analysis this service delivers, each on its own page.

All eleven types

How we work.

5 steps, from the first question to the delivered result.

Maps we made.

The caption under each map says whether it comes from a project we delivered or is an example analysis.

Bucharest and Ilfov county with built-up land coloured by when it first appeared, from dark purple for land built up by 1975, most of it inside the city, through pink and orange to yellow for 2010–2020, most of it in Ilfov around the city, and the land outside the study area dimmed

Example analysis on open data

Built-up growth 1975–2020, Bucharest and Ilfov, Romania

Built-up land by when it first appeared: cells at least 20% built up, km² in the study area

  • By 1975 (125 km²)
  • 1975–1990 (25 km²)
  • 1990–2000 (32 km²)
  • 2000–2010 (53 km²)
  • 2010–2020 (56 km²)
  • Bucharest + Ilfov (study area)
  • Bucharest city limit (dashed)
  • Lakes and rivers

Recent work.

All projects
U.S. counties grouped into sales territories

Market intelligenceUnited States · 2024

Automated U.S. territory design

Rice-field classification map in the Sacramento Valley

Satellite monitoringUnited States

Rice-field mapping, Sacramento Valley

Land-cover map of the project area in Mozambique, in Google Earth Engine

Satellite monitoringMozambique · 2024

Land cover & deforestation trends

Map of provincial high-speed internet projects by status, Ontario

Web GIS & appsCanada · 2023

Ontario high-speed internet geoportal

Questions about this service.

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01Can you automate our monthly data updates?

Yes — scheduled update systems are a core deliverable.

02Do you design spatial databases?

Yes — PostGIS/SQL database design from scratch or refactors.

03Can you process data in the cloud?

Yes — cloud-based spatial processing, including Google Earth Engine.

04Can automation live inside our web app?

Yes — we build processing into web apps and back ends.

05Do you build end-to-end pipelines?

Yes — from source ingestion to processed, ready-to-use outputs.

Guides for this service.

Articles from our project work that explain the method.

All articles

Other services.

All services

Ready to put your geospatial data to work?

Tell us the area, the decision and the deadline. We reply within 24 hours, from the person who will deliver the work.

Based in Bucharest, working with clients on five continents.

Start a projectSee our work