•Field survey, phenology model, airborne hyperspectral remote sensing were combined.•Remote sensing method using VNIR identified infested trees later than field survey.•Red-edge based indices (REIP, ANCB) were more sensitive during early infestation. Detection in the early phase of bark beetle infestation is a vital task for proactive management strategies, as practiced in most Central European forests, to minimize economic losses due to bark beetle infestation and to mitigate their further spreading. For this work, remote sensing methods are coming to be in great demand as an objective approach to enable monitoring bark beetle infestation even at individual tree level. This case study monitored bark beetle (Ips typographus) activity at local level in Norway spruce forest in the Czech Republic. The main aim of this study was to compare the remote sensing methods against classical field survey conducted by forest workers in detecting newly infested trees. To compare these two methods, an extensive field and aerial campaign was conducted in the southern part of the Czech Republic during 2020. Bark beetle infestation was monitored by traditional methods (i.e. field survey) on a weekly basis from mid-March to mid-September. During the same period, aerial scans were performed once per month (seven in total) using a CASI-1500 hyperspectral sensor (visible and near-infrared, 400–1000 nm) with spatial resolution of 0.5 m. This work mapped transition from healthy up to red attack of 75 Norway spruce trees that were infested during the same week. The same number of healthy trees were added to the data set for hyperspectral data analysis. Both groups were analysed by vegetation indices, with emphasis on effect caused in the canopy by bark beetles. The success rate for bark beetle detection is always associated with acquisition time. In order to define the optimal time for data acquisition, we employed a phenology model for I. typographus (RITY 2.0) to take into consideration bark beetle development. The results of the experiment showed that classic field survey detected infested trees earlier than did analysis using remote sensing data from the visible and near-infrared region. The difference was 23 days for the most successful indices (i.e. REIP, PRI, and ANCB650–720) in our test. Nevertheless, both methods detected the infested trees within 6 weeks after infestation, which is the recommended period for taking measures to prevent bark beetles from spreading further, and thus hyperspectral imagery can be used as a valid information source for bark beetle detection.