European Union GOV EN Fonduri UE ICAS

Project informations

EO-ROFORMON aims to prototype a novel national forest monitoring and forecasting system based on the integration of active (radar) and passive (optical) Earth-Observation (EO) sensors calibrated with in situ dataobtained from terrestrial laser scanning thus avoiding one of the main criticisms with respect to the ICP-Forests network, the consistency of assessments. The project, carried out in a representative study area, will focus on retrieving indicators related to forest condition/status (e.g. defoliation) and degradation (e.g. logging activity, wind throws, fires). Changes in canopy water content would be also monitored to provide an early-warning system on forest condition trends. The project aims to differentiate forest defoliation (caused by natural disturbances) from degradation (from logging activities) by taking advantage of the temporal dimension of changes in the remote sensing signal from optical and radar data. Thus, spatially explicit information on forest condition, logging extent, intensity and their timeline will become available.

The project will also develop predictive models adapted to Romanian forest conditions for studying the evolution of the forest fund using historical and present information of forest status, forest management practices as well as the natural and anthropogenic disturbances.Such an objective will be achieved through forest landscape modelling using specific models (e.g. LANDIS-II). The LANDIS-II model shall be calibrated with species specific allometry, disturbance regimes and management conditions characteristic for the Romanian forests.

EO-ROFORMON will address data-to-information-to-decision-making process for forest ecosystem monitoring, making significant progress beyond the state of the art, using novel approaches of Earth System and Natural Sciences. More specifically, the project has the objectives and the capacity to:

  1. Make extensive use of Earth Observation data in combination with in situ Data from new EO missions (in particular, Sentinel-1/2 sensors) and from ground-based monitoring will be utilized to provide a spatially explicit and consistent picture of the state and changes in forest condition (for the selected study area) which is closely related to biodiversity, natural capital and ecosystem services.
  2. Create a corpus ofinnovative, field-tested, peer-reviewed and documented EO based monitoring methodology to define forest status andappraise future trends through forest landscape simulation models (e.g. LANDIS-II) with a special emphasis on Romanian forest management practices and policy needs.
  3. Develop a conceptual framework guiding the integration of data, models and scenarios towards a new vision of forest monitoring and landscape modelling.
  4. Improve evidence-based environmental policy making, enhancing administrative efficiency and contributing to transparent decision-making. Project results will directly benefit resource managers and active community stakeholders.
  5. Efficientcapacity building through the formation of specialized researchers with expertisein terrestrial laser scanning, remote sensing, time-series analysis and forest landscape modelling.