Next week, the European Environment Agency (EEA) and the European Space Agency (ESA) will organize the second edition of the conference on Earth Observation for Monitoring, Reporting and Verification of Carbon Removals (EO4MRV). Held in Copenhagen, Denmark, on the 7-10 October 2025, the conference will bring together experts from across disciplines (scientific research, national GHG inventories, policy, and the private sector) to share insights, innovations, and experiences that support robust MRV (Monitoring, Reporting, and Verification) systems for carbon removals in the EU.
Jukka Miettinen
45 posts
Over the past years, the Forest Carbon Monitoring project (FCM) has been pioneering remote sensing-based, user-centric approaches for monitoring forests. By combining satellite imagery with reference data and scientific rigor, the project has been shaping a new era of forest carbon monitoring that is not just innovative, but practical and scalable.
The summer holiday season starts to be over, and we are entering the final three months of the Forest Carbon Monitoring (FCM) project. Publication of the FCM tools is one of the main objectives for the remaining time. You may have seen the term Forestry TEP mentioned several times on the FCM website. It is the processing platform where the FCM use case demonstrations have been run. It will also be the main interface to access the FCM tools after the project has ended.
At the Living Planet Symposium 2025, a packed Room 0.14 came to life early Thursday morning as stakeholders from across the forest, climate, and remote sensing sectors gathered for a networking session titled “Unlocking the Power of EO for Forest Carbon Monitoring.” Hosted by the European Space Agency’s Forest Carbon Monitoring (FCM) project, the session combined expert presentations, dynamic panel discussions, and audience engagement, showcasing how Earth Observation (EO) is transforming forest biomass and carbon monitoring.
One of the main objectives of the FCM project continuation was to extend the temporal range of the pan-European growing stock volume (GSV), above ground biomass (AGB) and below ground biomass (BGB) maps. We are happy to announce that this objective has been achieved as a set of new pan-European maps have been made available in the FCM product portal.
Forests play a vital role in regulating our climate, but monitoring their health and carbon storage is no simple task. In a new video from the Forest Carbon Monitoring (FCM) Project, users from two very different regions — Catalonia in Spain and the Colombian Amazon — share how they are working with the project’s Earth Observation tools to improve forest management and support climate action.
Join us at the upcoming Living Planet Symposium (LPS 2025) for a dynamic networking session showcasing our European Space Agency’s Forest Carbon Monitoring (FCM) project and our versatile toolset for Earth Observation (EO)-based forest biomass and carbon monitoring. Designed to support a wide spectrum of forestry stakeholders, our FCM tools address key needs from policy compliance reporting (e.g. CRCF, LULUCF), voluntary private-sector reporting, to scientific applications including digital twins and ecosystem analysis.
Last autumn, we had a visiting scientist from the University of Oviedo staying here at VTT. This gave us a great opportunity to test some of the FCM tools in his study areas in northern Spain, and thereby provided valuable information on the applicability of the methods in new areas.
One of the main objectives of the continuation phase of the FCM project is to include a deep learning method in the tool portfolio. Based on earlier experiences, the UNet model family approaches were selected. A vanilla UNet model as well as a more advanced SeUNet model with a squeeze-excitation block have been tested and further developed in the Catalonia and Norway demonstration areas. The idea is to
EO data products are sensitive to variations caused by atmospheric or seasonal effects, sometimes significantly affecting forest variable predictions. When used repeatedly in the same area to monitor the development of forest resources these effects can cause inconsistencies in the time series. The Data Assimilation (DA) approach to be demonstrated in the Norway use case aims to mitigate these inconsistencies of forest variable values in the monitoring time series.