Potential of Unmanned Aerial Vehicle Red-Green-Blue Images for Detecting Needle Pests: A Case Study with Djak (Lepidoptera, Geometridae).

Djak (Lepidoptera, Geometridae) is a leaf-feeding pest unique to Mongolia. Outbreaks of this pest can cause larch needles to shed slowly from the top until they die, leading to a serious imbalance in the forest ecosystem. In this work, to address the need for the low-cost, fast, and effective identification of this pest, we used field survey indicators and UAV images of larch forests in Binder, Khentii, Mongolia, a typical site of Djak pest outbreaks, as the base data, calculated relevant multispectral and red-green-blue (RGB) features, used a successive projections algorithm (SPA) to extract features that are sensitive to the level of pest damage, and constructed a recognition model of Djak pest damage by combining patterns in the RGB vegetation indices and texture features (RGB) with the help of random forest (RF) and convolutional neural network (CNN) algorithms.