Advancing satellite-derived environmental intelligence

This project will enhance the scalability and accuracy of satellite-derived environmental intelligence by implementing an operational feature density scaling workflow within GeoNadir. By leveraging high-resolution reference data, we will deploy AI-driven models to improve quantitative habitat and vegetation assessments from Sentinel-2 imagery. This will
move beyond traditional categorical classifications for terrestrial and marine environments (e.g., “vegetation”, “coral”, “seagrass”) and instead provide precise percentage-based coverage of key environmental features.
Over six months, we will integrate automated Sentinel-2 image selection, feature density calculation, and visualization tools into GeoNadir, ensuring users can efficiently scale localized high-resolution data to broader satellite observations. The outputs will include an intuitive
analysis toolset, enabling industry users in biodiversity monitoring, fisheries, natural capital assessment, and environmental compliance to extract actionable insights from satellite data. By embedding this workflow directly into an existing commercial SaaS platform, the project
will deliver an immediately usable and scalable EO solution for industry and government stakeholders.