The THEIA API offers customisable geospatial data streams that integrate seamlessly with non-geospatial platforms. It gives developers and data scientists flexible access to environmental data such as weather, fire risk, and vegetation indices. Designed for integration with third-party software services, the API features unique data types and can be extended to meet specific user needs.
Customisable geospatial data streams for seamless integration.
Users can access global datasets with ease — subscribing only to the regions that matter — and deploy advanced geospatial analysis, including Earth Observation processing and AI-powered mapping.
View our technical use cases from the API's data
Global vs. Local Wildfire Risk Models
Most international fire danger systems – like the Canadian FWI – were designed for large-scale forest fires. They perform well in many places, but Scotland’s unique climate and ecology don’t fit within the system. Scotland's landscape is dominated by heather moorland and peatlands. Counterintuitively, heath plants like heather dry out over winter, making spring the riskiest season. Dry plant dander and shrubs ignite easily, sometimes sparking long-burning peat fires that are difficult to control. Thus, one of the FWI’s sub-indices – the Fine Fuel Moisture Code (FFMC) – is more relevant locally.
At EOLAS Insight we model all FWI sub-indices using weather data to deliver more detailed, localised fire risk insights. Until all of us adapt, Scotland’s wildfire risk will remain under-represented – and we’ll stay under-prepared. It’s time to rethink how we measure and manage fire risk here. Subscribe to our API to enhance your data science and insights.
Analysing Storm Eowyn to Support Damage Assessment
From 23 to 26 January, Storm Eowyn swept northeast across the Atlantic, bringing powerful winds to Ireland and western Scotland. To support storm damage investigations, we analysed hourly wind data from the Met Office, focusing on both speed and direction.
Wind speeds ranged from complete calm up to a peak of 44 m/s — a significant force capable of structural damage, especially in exposed coastal areas. Using U and V wind components, we visualised the storm’s progression in an animated map. A blue-to-red colour gradient illustrated wind intensity, while directional traces revealed Eowyn’s evolving path over time.
The most intense phase occurred on the evening of 24 January, with strong southwesterly winds striking western coastlines. Interestingly, the highest gusts were recorded after the cyclone’s centre had passed — a post-storm surge often associated with widespread damage. These insights are valuable for pinpointing when and where the most severe impacts likely occurred.
By combining detailed wind analysis with visual tools, this approach supports faster, more informed storm damage assessments — helping insurers, planners, and responders better understand and react to extreme weather events.
