Enhancing BigQuery Geospatial with Earth Engine Raster Analytics and Map Visualisation
- 28East
- Sep 19
- 3 min read
Geospatial analytics can turn data into actionable insights that drive sustainable business strategy and smarter decision-making.
During Google’s Cloud Next 2025 event, they announced the preview of Earth Engine in BigQuery, an extension of its current geospatial offering. This tool is focused on enabling data analysts to combine existing structured data with geospatial data from satellite imagery.
With this new set of tools, geospatial analysis is more accessible to data professionals everywhere. This blog dives into these insights in more detail.
Bringing Earth Engine to Data Analysts
Earth Engine in BigQuery makes it easier for data analysts to bring satellite and environmental data into their existing workflows.
You can now combine raster data, like satellite imagery or climate models, with vector data, like boundaries, roads, or infrastructure, directly in BigQuery, removing the need for complex setups.
This unlocks new use cases like tracking disaster risk over time, planning infrastructure based on climate impact, or improving supply chain decisions with weather insights.
The first release includes two key features:
ST_RegionStats(): A new geography function that helps you calculate stats within custom regions.
Earth Engine datasets in BigQuery Sharing: A growing library of 20+ ready-to-use datasets, covering land cover, weather, and climate risks, all available directly in BigQuery.
What’s New in Earth Engine?
With Earth Engine now generally available in BigQuery, users get access to even more features that make working with geospatial and environmental data easier and more flexible:
Wider regional support: Earth Engine in BigQuery now runs in both US and European regions, giving you more control over where your data is stored and processed.
Richer dataset insights: A new Image Details tab in BigQuery Studio makes it easier to explore raster datasets. You can now view detailed metadata, such as band information and image properties, directly in your workspace.
Better usage management: You can now track slot-time usage for each job and set quotas to control your Earth Engine usage in BigQuery, helping you stay on top of budgets and avoid surprise costs.
A New Way to Visualise BigQuery Data
Google has introduced map visualisation in BigQuery Studio, making visualising geospatial data more useful for real-world workflows.
The newly renamed “Visualisation” tab, previously “Chart”, now includes the ability to display geospatial query results on a Google Map.
This makes it easier to explore data visually and spot patterns faster. With this update, you can:
See results instantly on a map as soon as your query runs.
Interact with the map to inspect results and debug queries in real time.
Customise the styling to highlight the insights that matter most.
All of this is built directly into BigQuery Studio, making geospatial analysis simpler, faster, and more accessible for both analysts and developers.
Embrace the Future of Geospatial Analysis with 28East
With Earth Engine now fully integrated into BigQuery and map visualisation available in preview, geospatial analysis has never been more accessible. These tools make it easier to turn raw data into meaningful, real-time insights that support smarter decisions.
At 28East, we help African businesses tap into this growing ecosystem of location intelligence, combining local context with global tools to solve real challenges.
If you're ready to start building location-powered solutions, 28East is here to help you every step of the way. Reach out to see how we can help!
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