Spatial, spectral and temporal insights: harnessing high-resolution satellite remote sensing and artificial intelligence for early monitoring of wood boring pests in forests

Globally, biotic factors like insect pests and diseases as well as abiotic factors like fire, windstorms, and droughts influence the global forest ecosystem. Wood-boring pests (WBPs) pose a considerable threat to forest ecosystems worldwide owing to their capacity of remaining unnoticed during early stages, resulting in vast and pervasive infestations during later stages, eventually resulting in significant tree death. Therefore, it is crucial to promptly and effectively treat early-stage WBPs by timely detection. The prompt detection of WBPs requires the use of advanced and effective methods, such as remote sensing. This paper provides an overview of the many uses of several remote sensing devices, platforms, and detection algorithms in the context of monitoring WBPs infestations. Modern lightweight sensors such as light detection and ranging (LiDAR), hyperspectral imagers, thermal cameras, and radio detection and ranging (Radar) combined with unmanned aerial vehicles (UAVs) with versatile capabilities offer a comprehensive and effective method for gathering data. The purpose of this study is to examine the current capabilities, limits, and potential future advancements in accurately and promptly identifying WBPs.