The application of Unmanned Aerial Vehicles (UAV) in combination with optical sensors for forestry monitoring is a rapidly developing field that offers new opportunities for plant health management. Collecting multispectral data with UAVs creates an opportunity to enable frequently available high-resolution data, which is essential for the monitoring of insect pest damage. Multispectral sensors can capture damage levels based on different spectral wavelengths ranging from visible to shortwave infrared.
Gonipterus sp. n. 2, commonly known as the Eucalyptus snout beetle, is a leaf-feeding insect pest of Eucalyptus, native to Australia. An egg parasitoid, Anaphes nitens, is used as classical biological control agent for Gonipterus sp. n. 2. Sporadic outbreaks can have economic impacts on the forestry industry. The ongoing research project aims to develop an early detection model to detect Gonipterus sp. n. 2 damage using UAV and satellite data. UAV flights of Gonipterus trials have been done during summer of 2021 and 2022 in collaboration with researchers at the Institute of Commercial Forestry Research (ICFR), University of Ghent and Institut für Zuckerrübenforschung.
During the week of 16-21 October, a team of FABIans including Boitshoko Rammuki (MSc candidate), Edwin Wanjofu (MSc candidate), Phumlani Nzuza (PhD candidate) and Josias Letaonana (Field extension officer) travelled to Melmoth to assess Gonipterus sp. n. 2 damage levels on both young and old Eucalyptus dunnii compartments using an Unmanned Aerial Vehicle (UAV) and to sample damage levels used for validation purposes. High-resolution RGB data (visible spectral wavelength constituting red, green and blue channels) was tested to complement multispectral data to improve the detection of Gonipterus sp. n. 2 damage. Spectral signatures collected during ad hoc surveys of Gonipterus outbreaks together with data collected from the ICFR trials can be used to develop models to detect Gonipterus damage using UAVs.
We are grateful for the help and support we received from Jolanda Roux, Mhlengi Gumede and Ciniso Magagula.