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We contribute to climate change mitigation activities by developing a platform for forest carbon monitoring with high accuracy, reach and frequency

The project

Forests are essential in maintaining healthy ecosystem interaction and biodiversity on Earth. They are in a key role in the fight against climate change since they can restore increasing carbon stocks. Hence, several national and international initiatives (including the UNFCCC Paris Agreement and the EU LULUCF Regulation) require regular reporting of forest biomass and carbon. Robust, reliable and transparent monitoring approaches of forest biomass and carbon are needed to respond to reporting requirements.

The Forest Carbon Monitoring project will develop and implement a prototype of a reliable and cost-efficient monitoring and accounting platform for forest carbon stock based on satellite remote sensing approaches supported by in-situ datasets.

Close integration of field data and remotely sensed data. Statistically sound monitoring methods.
Ecosystem process-based carbon modelling integrated into the system, allowing future inclusion of additional carbon flux and forecasting features.

Flexibility towards user requirements ranging from private company carbon balance monitoring to continental level analyses with publicly available datasets.

Why remote monitoring?


Spatially detailed data from large forest areas — also regions without proper forest inventory data.


Openly available satellite datasets used together with published monitoring methods.


Enabling high resolution mapping and monitoring of global forests.


Reaching global scale with frequent data acquisition and long-term standardized systems at low cost.


Latest posts

Time series Romania

Platform prototype demonstrations concluded

Another major milestone has been reached in the project, with all the eight main demonstrations successfully concluded. Altogether, 79 prototype map products were delivered to the users in the demonstrations, including forest structure variables, biomass and growth variables and change detection products.

Interested in knowing what is happening?