  Remote sensing is the process of detecting and monitoring the physical
characteristics of an area by measuring its reflected and emitted radiation at
a distance. It is being broadly used to monitor ecosystems, mainly for their
preservation. Ever-growing reports of invasive species have affected the
natural balance of ecosystems. Exotic invasive species have a critical impact
when introduced into new ecosystems and may lead to the extinction of native
species. In this study, we focus on Ludwigia peploides, considered by the
European Union as an aquatic invasive species. Its presence can negatively
impact the surrounding ecosystem and human activities such as agriculture,
fishing, and navigation. Our goal was to develop a method to identify the
presence of the species. We used images collected by a drone-mounted
multispectral sensor to achieve this, creating our LudVision data set. To
identify the targeted species on the collected images, we propose a new method
for detecting Ludwigia p. in multispectral images. The method is based on
existing state-of-the-art semantic segmentation methods modified to handle
multispectral data. The proposed method achieved a producer's accuracy of 79.9%
and a user's accuracy of 95.5%.
