Airborne Scanning

Invasive species significantly impact ecosystems, which is fostered by global warming. Their removal generates high costs to the greenery managers; therefore, quick and accurate identification methods can allow action to be taken with minimal impact on ecosystems. Remote sensing techniques such as Airborne Laser Scanning (ALS) have been widely applied for this purpose.

However, many species of invasive plants, such as Acer negundo L., penetrate the forests under the leaves and thus make recognition difficult. The strongly contaminated riverside forests in the Vistula valley were examined in the gradient of the center of Warsaw and beyond its limits within a Natura 2000 priority habitat (91E0), namely, alluvial and willow forests and poplars. This work aimed to assess the potentiality of a dual-wavelength ALS in identifying the stage of the A. negundo invasion.

The research was carried out using over 500 test areas of 4 m diameter within the riparian forests, where the habitats did not show any significant traces of transformation. LiDAR bi-spectral data was acquired with a RIEGL VQ-1560i-DW scanner, which is able to record data in the green (532 nm) and the near-infrared (1064 nm) wavelengths. The measurement density for both channels was 6 points/m2. The data were classified using the convolutional neural network model developed at OPEGIEKA Sp.z.o.o.

The full article is published on the platform MDPI, and can be found here.