Integrating environmental variables and WorldView-2 image data to improve the prediction and mapping of Thaumastocoris peregrinus (bronze bug) damage in plantation forests

This study integrated environmental variables together with high spectral resolution WorldView-2 imagery to detect and map Thaumastocoris peregrinus damage in Eucalypt plantation forests in KwaZulu-Natal, South Africa. The WorldView-2 bands, vegetation indices and environmental variables were entered separately into PLS regression models to predict T. peregrinus damage. The datasets were then integrated to test the collective strength in predicting T. peregrinus damage. Important variables were identified by variable importance (VIP) scores and were re-entered into a PLS regression model. The VIP model was then extrapolated to map the severity of damage and predicted T. peregrinus damage with an R2 value of 0.71 and a RMSE of 3.26% on an independent test dataset. The red edge and near-infrared bands of the WorldView-2 sensor together with the temperature dataset were identified as important variables in predicting T. peregrinus damage. The results indicate the potential of integrating WorldView-2 data and environmental variables to improve the mapping and monitoring of insect outbreaks in plantation forests. The result is critical for plantation health monitoring using a new sensor which contains important vegetation wavelengths.