Zastosowanie danych z satelity Sentinel-2 do szacowania rozmiaru szkód spowodowanych w lasach huraganowym wiatrem w sierpniu 2017 roku

Extreme weather events such as hurricanes, floods or fires become more and more common phenomena in Europe. In August 2017, strong wind accompanied by heavy thunderstorms caused severe damage over the large area in central and western Poland. According to rapid damage assessment prepared by the State Forests authorities a few days after the windthrow, ca 79.7 thousand hectares of forest was damaged and 9.8 million of cubic meters of wood was lost. Assessment of such a large−scale forest damage is difficult without using the remote sensed data. In this study, we examined the potential of the European satellite Sentinel−2 data for assessment of the forest damage caused by the windthrow. The assessment was performed using a difference between a normalized difference moisture index (NDMI) calculated based on the pre− and post−damage Sentinel−2 images. NDMI was calculated based on NIR (824 nm) and SWIR (1610 nm) bands. The result of this study showed the total damage area in forest is equal to 35.8 thousand hectares, of which 27.7 thousand hectares was damaged within the State Forests and 8.1 thousand hectares outside the State Forests administration. These figures are much lower than the estimates by the State Forests, regarding the forest damage within the State Forests and higher comparing to estimations in the non−state forest. In fact, these figures are comparable with the heavily damage areas assigned to clearance by the State Forests. The accurate comparison of the results was not possible due to the lack of up−to−date information on forest damage. Sentinel−2 data revealed to be perfect data for large scale damage assessment and post−damage forest monitoring mainly due to the wide swath up to 290 km. The limitation of the optical sensors is the cloudiness. Unfortunately, in the case of this analysis, the first cloud free image was acquired 6 weeks after the windthrow. It reduces the potential of the single−source data for rapid assessment of damages.