The rapid spread of invasive plant species (IPS) over several decades has led to numerous impacts on biodiversity, landscape and human activities. Early detection and knowledge on their spatiotemporal distribution is crucial to better understand invasion patterns and conduct appropriate activities for landscape management. Therefore, remote sensing provides great potential for detecting and mapping the spatial spread of IPS. The study presents a mapping of IPS (Reynoutria japonica and Impatiens glandulifera) over the last decade, on two sites located in the central Pyrenees in the southwest of France, from very high resolution RGB aerial photographs. A supervised classification based on the random forest algorithm was performed using pixel attributes. The original spectral bands (RGB) were used, to which vegetation indices and textures were added to improve the detection. The classification models yielded a mean prediction accuracy (F-score) of 0.90 (0.87 to 0.92) at the site 1 and 0.87 (0.81 to 0.91) at the site 2. Results show that the expansion of IPS is closely related to the presence of corridors (e.g., roads, power lines) and to environments disturbed by human activity such as land clearing.