 This study applied a method based on inter-annual phonology of Norway's Bruce Stans derived from synthetic multispectral data to part of the Bavarian Forest National Park in Germany. The study fused temporarily continuous moderate-resolution imaging spectridiometer and discrete rapid eye data using a flexible spatiotemporal data fusion method to achieve validated 8-day rapid eye-like composites of normalized difference vegetation index for 2011. The study assumed that the dead trees delineated on 2012 aerial photographs were those in which bark beetle infestations were initiated in 2011. Samples were drawn with variable-sized buffering to represent the areas prone to infestations and their surroundings. The study applied a conditional inference random forest to select the best image date among the entire 46 synthetic datasets to best discriminate between the core infestation patches and their surroundings from the subsequent year. Of the discrete time points identified, day 281 of the year represented the highest discrepancy between aerial image-based dead trees and their surroundings. Classification results were significantly correlated with beetle count data obtained using pheromone traps. The study provided valuable information for management purposes and enabled wall-to-wall mapping of Stans prone to infestation and its uncertainty. The results offer potential implications for rapid and cost-effective monitoring of bark beetle outbreaks using satellite data which would be of great benefit for both management and research tasks. This article was authored by Human Latifi, Torsten Doms, Burkhard Budet and others. We are article.tv, links in the description below.