<p> Invasive species have developed long-term relationships with humans, especially since the start of the Industrial Revolution, and they have caused immense damage to native environments, ecosystems, and economies. An emerging invasive insect that has recently gained considerable attention is the spotted lanternfly (SLF). Early detection of SLF infestations in new areas or at low densities can lead to a more efficacious management and reduce costs associated with control them. Developing approaches to detect the presence of invasive species, favorable habitats for their establishment, and predicting potential spread will be crucial for effective management strategies to protect native environments and the economy. The goal of my thesis is to improve the understanding of how spotted lanternfly changes the spectral profile and chemical composition of host tree species. I found that spotted lanternfly feeding influences host canopy chemical and spectral properties. Specifically, I was able to use leaf-level hyperspectral measurements to differentiate SLF infestations levels in silver maple and red maple, shown by my first chapter, along with black walnut in my second chapter. Further, I was able to find differences in phenolic compounds in response to SLF infestations in red maple. The results of my study have the potential to be scaled up from leaf-level to landscape-level measurements. I have identified spectral signatures in red maple, silver maple, and black walnut that can be used to identify infestations from spectral data collected from UAVs or satellites. This potentially provides a new method for detection that is easier than traditional ones (like manual scouting and trapping). </p>