ABSOLUT SENSING develops satellite-based observation technologies that provide precise environmental, geo, and planetary intelligence services. Their solutions deliver accurate data for monitoring ecological changes and managing natural resources, essential for informed environmental decision-making.
Funding
Funding not disclosed
EAFounders
Product
Problem
Monitoring changes in the Earth's biosphere, atmosphere, and geosphere requires accurate and high-resolution data, which is often limited by the capabilities of traditional satellite-based observation technologies. Existing solutions may lack the sensitivity and precision needed for effective environmental monitoring and resource management.
Solution
Absolut Sensing develops miniaturized, high-performance hyperspectral instruments and satellite constellations for precise environmental, geo, and planetary intelligence. Their core offering includes the GESat constellation, designed for accurate, high-resolution methane emissions monitoring. By integrating miniaturized and cooled hyperspectral instruments compatible with standard Cubesat platforms, Absolut Sensing enables more frequent and reliable monitoring of atmospheric changes. The company leverages physics-guided machine learning models trained on extensive atmospheric data to forecast changes and emission rates with improved accuracy.
Target Audience
The primary target audience includes regulators and businesses requiring precise methane emissions monitoring, as well as commercial operators and developing countries seeking to deploy their own Earth observation constellations.
Features
- GESat data: High-resolution methane concentration and emission data for facility-scale quantification.
- CMI
- Certified Emissions Inventory: Streamlines methane emissions inventory production and validation.
- PLUM
- Methane Intelligence Platform: Facilitates retrieval, analysis, and sharing of emissions information.
- Miniaturized spectro-imager with a high-performance cryogenic sensor and forward-compensation scan mirror.
- Physics-guided machine learning models for forecasting atmospheric changes and emission rates.
- CRYASSY: Compact cryogenic set for enhanced measurement sensitivity in comparison to non-cooled instruments.
- Integrated filter-sensor detection systems for applications ranging from SWIR to LWIR.
- Miniaturized optical systems designed for smallsat applications.