This dataset comprises forest inventory (diameter at breast height, tree height, social class and relative crown distance) and tree canopy health data (extent of overall damage, discolouration and defoliation) collected in 2021 from sites within core protected areas of the UNESCO Rhӧn Biosphere Reserve dominated by European beech (Fagus sylvatica) forest. The study forests were subject to the extreme drought event that impacted central Europe in 2018/2019 and this project sought to collect data to enable the analysis of individual tree and stand level characteristics that influence the response (canopy damage and defoliation) of European beech trees to extreme drought events. Field assessments of individual tree and stand canopy health were carried out within this project collecting data comprising canopy condition assessments and measurements of individual tree size and stand demography. The work was supported by the Natural Environment Research Council (Grant NE/V00929X/1). Full details about this dataset can be found at https://doi.org/10.5285/4df17a8f-9854-4b6e-8578-d99fbefb1352

This dataset comprises four RGB unmanned aerial vehicle (UAV) images collected in September 2020 of European beech (Fagus sylvatica) forest within core protected areas of the UNESCO Rhӧn Biosphere Reserve, Germany. The study forests were subject to the extreme drought event that impacted central Europe in 2018/2019 and this project sought to collect data to enable the analysis of individual tree and stand level response (canopy damage and defoliation) of European beech trees to extreme drought events. The RGB images available in this dataset have approx. 3cm pixel size with an associated 10cm pixel digital elevation model (DEM) and are suitable for identifying individual trees and the degree of canopy damage (defoliation, discolouration, and mortality) sustained by individuals/stands within the forest. The work was supported by the Natural Environment Research Council (Grant NE/V00929X/1). Full details about this dataset can be found at https://doi.org/10.5285/b2d17962-3c7f-4193-a180-cde885d1a83e