Remotely piloted aircraft system (RPAS) platforms are able to optimize the process of acquiring aerial images and improve the quality of the products generated in terms of spatial and temporal resolution. The exponential advance of the use of RPAS platforms in forestry, especially from the year 2010, is noteworthy. In this review, we present the global state of the art of the development and applications of RPAS technology in forestry, structured from a systematic review. Our results reveal a trend towards the use of multirotor RPAS platforms compared with fixed-wing platforms and that sensors that register in the visible spectral range are still the most widely used. More recent research has shown applications geared especially for areas such as forest inventory, with many innovations based on the detection of individual trees. Special focus has also been given to new alternatives for pest and disease mapping and phenological phenomena that occur at short intervals, as well as the monitoring of fires and postharvest areas. Therefore, there is a great potential for the use of RPAS platforms in a wide range of forest applications, whether linked to the productive sector or to the conservation of biodiversity, with great advances for spatiotemporal forest monitoring and expectations of further progress for the coming years.

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Invasive species are known to have potential advantages over the native community and can be expressed in their leaf functional traits. Thus, leaf-level traits with spectral reflectance can provide valuable insights for distinguishing invasive trees from native trees in complex forest environments. We conducted field spectroscopy measurements in a subtropical area, where we also collected trait data for 12 functional traits of invasive (Psidium guajava and Hovenia dulcis), and native species (Psidium cattleianum and Luehea divaricata). We found that photosynthetic pigments were responsible for the greatest interspecific variability, especially in the green region of the spectrum at 550 nm, therefore contributing to detection of invasive species. In addition, according to LDA and stepwise procedures, the most informative reflectance spectra were concentrated in the visible range that is closely related to pigment absorption features. Furthermore, we aimed to understand the leaf optical properties of the target invasive species by using a combination of narrow bands and linear regression models. P. guajava showed high correlations with specific leaf area, Car/Chl and relative water content. H. dulcis had a strong correlation with water content, specific leaf area and Chla/Chlb. Overall, this methodology proved to be appropriate for discriminating invasive trees, although parameterization by species is necessary.