Earth observation monitoring to support to the sustainable management of natural, semi-natural and planted forests
Forests are valuable and irreplaceable ecosystems, which play an important role both from an ecological, social and economic perspective. They serve as habitats for two thirds of terrestrial animal and plant species, are home to many indigenous people and the timber industry is fundamental in many regions. By absorbing and storing atmospheric carbon, forests are crucial for the global carbon cycle and in the moderation of atmospheric greenhouse gases. They prevent soil erosion and water run-off and provide the local population incentives for a sustainable livelihood. Monitoring of forests is essential for a better understanding of this valuable ecosystem.
Deforestation and forest degradation continue to take place at alarming rates, which contributes significantly to the ongoing loss of biodiversity and affects forest ecosystems services. Fires, forest pests and climate change are also contributing to the degradation and loss of forests around the world, in addition to the alarming deforestation figures. Thus, there is an urgent need for effective strategies to reduce deforestation and forest degradations and implement sustainable forest management practices.
Sustainable forest management
Forest monitoring shall be addressed on local, national, continental and global level. Earth observation data provide information on forest extent, types and changes over time. Multiple EO based indicators can be derived to support mapping and monitoring of forest areas, net changes, above-ground biomass stocks and additional forest parameters on the forest management and conditions.
Forest loss and recovery monitoring
EO services are based on the integrated analysis of a dense and continuous time-series of optical and radar satellite data aiming to capture the complexity of the forest loss and regrowth phenomena in temperate and tropical forest. The products provide spatially and temporally explicit estimates of change, the type and severity of change, and the associated uncertainty in estimates.