Imagine a giant, digital filing cabinet that automatically organizes nature data from satellites, cameras, and sensors into easy-to-read 3D maps. Instead of digging through messy spreadsheets, users can instantly see how wildlife and plants are changing over time in a specific area. It's like having a real-time weather map, but for the health of the planet's ecosystems.
Companies struggle to quantify biodiversity loss and ecosystem degradation due to fragmented data from different sources. This makes it difficult to comply with environmental regulations or manage natural resources sustainably.
A cloud-based infrastructure featuring biodiversity data cubes and standardized workflows to integrate satellite, sensor, and citizen science data.
If you are a sustainability auditing firm dealing with fragmented client data on land use — this project developed biodiversity data cubes that organize species occurrences over time and location. This allows you to identify trends and data gaps with greater accuracy for your clients.
If you are a large-scale agribusiness dealing with the need to prove sustainable resource management — this project developed cloud computing workflows that integrate satellite and sensor data. This helps you proactively respond to biodiversity loss and reduce the costs of manual monitoring.
If you are an environmental risk insurer dealing with unpredictable ecosystem degradation — this project developed state-of-the-art prediction models of biodiversity. This enables you to use reliable indicators to evaluate the risk of land-use changes and pollution.
Based on available project data, the project promotes open-access platforms, but specific commercial pricing is not mentioned.
Yes, the project uses cloud computing environments and the Global Biodiversity Information Facility (GBIF) infrastructure to ensure the tools are accessible at a global level.
Based on available project data, the project emphasizes open-access and interoperable outputs to ensure transparency and widespread use.
The system is designed to integrate diverse sources including automatic sensors, camera traps, eDNA, and satellite tracking into a standardized data cube format.
The project is active from 2023-03-01 to 2026-08-31, meaning tools are currently being developed and refined.
The consortium is heavily research-oriented, consisting of 7 universities and 4 research institutions, with only 1 industry partner and 2 SMEs. This 8% industry ratio indicates the project is primarily focused on scientific validation and technical development rather than immediate commercial productization, though the inclusion of 10 countries suggests a broad geographical validation of the tools.
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