Maximizing forest value through using Sentinel-2 in combination with hyperspectral UAVs

The global forest economy is subject to a number of threats to its production value. Forest diseases keep emerging due to globalisation and climate change - they are difficult to contain and mitigate. According to FAO, in the period 1980-2002 more than 52 mill. hectares of forest in 37 countries were damaged by pests. Now the Pine Wilt Nematode is estimated to have the potential to spread to 34% of Europe by 2030. These changes are costing not only society, but also forest owners and managers. In Portugal, forest owners are fined 44,000 EUR by the government if they do not clear-cut diseased trees within 15 days. Forest fires are escalating in severity and costs due to climate changes. Europe lost in 2017 three times as large an area to forest fires than during the period 2008-2016 in total. The forest fires cost Portugal alone more than 200 mill. EUR and killed at least 66 people in 2017. These threats to the forest economy require accurate, precise and frequent information for monitoring their status and planning any relevant mitigation actions. Sentinel-2 becoming operational in 2015, and the impressive results of deep learning techniques, served as an ideal starting point for the automated forest monitoring service Silvisense. As its products were demonstrated with pilot customers in Portugal and Norway, it became clear that adding airborne hyperspectral acquisitions would increase the capacity to detect disease outbreaks at an earlier stage. An earlier detection would enable more efficient mitigation measures to take place and preserve a greater volume of high quality standing wood. This is the basis for the H2020 project FOCUS. The paper describes how FOCUS is expected to add value to forest monitoring in Europe through enhancing interpretation of Sentinel-2 satellite data by combining it with hyperspectral airborne measurements