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Forest disturbance in Europe, induced by European spruce bark beetle Ips typographus, L., results in regionalscale dieback. Early stress detection in Norway spruce stands caused by bark beetle infestation at the green attack stage (when trees are yet to show distinct symptoms observable by the human eye) is crucial and can lead to improved forest management and reduced economic losses. This study aims to investigate and understand the dynamics of leaf traits and reflectance of Norway spruce (Picea abies) trees during bark beetle attack. Using high-resolution temporal images from RapidEye and SPOT-5 in parallel with the collection of field data, we examined which spectral regions and leaf traits are affected by infestation over time and how they help the discrimination between healthy and infested plots at the early stage of the attack. To achieve this aim, we used a novel approach by targeting both leaf and canopy level. We measured leaf reflectance spectra and six leaf traits (water content, nitrogen, chlorophyll fluorescence, chlorophyll and stomatal conductance) from 66 (30 plots) healthy and 54 (8 plots) infested trees at three consecutive time measurements in the summer of 2015 in the Bavarian Forest National Park. Concurrently, canopy reflectance and spectral vegetation indices (SVIs) were extracted from the selected plots (30 healthy plots) using seven RapidEye images and six SPOT-5 images. For the infested plots, in addition to the field measured plots (8), canopy spectral reflectance were extracted from the reference infestation data (291 plots) obtained through visual interpretation of high-resolution aerial photographs. Results demonstrated significant differences (p < 0.05) in the studied leaf traits between healthy and infested samples, and these differences increased with the progression of infestation. We found that leaf and canopy reflectance were significantly higher (p <= 0.05) for the infested trees by bark beetle than the healthy ones in the 'red edge' (680-790 nm) and 'shortwave infrared' (1110-1490 nm) spectrum throughout the infestation event. Our results further demonstrated that the spectral vegetation indices calculated from the red-edge and SWIR spectral bands, such as NDRE, DSWI, LWCI and NDWI, were able to differentiate between healthy and infested trees earlier than the other SVIs. The new insight offered by these results is that the red-edge and SWIR spectral information from multispectral satellites has the potential to considerably improve monitoring and detection of forest stress and has important implications for European field bark beetle management and future studies.