Objective By analyzing the hyperspectral features of Pinus yunnanensis in different damage levels and building monitoring models, to establish the damage monitoring model and judgment rules for integrated control of Tomicus yunnanensis.

Method In shoot damage period of T. yunnanensis, the imaging hyperspectral data of young and middle-aged P. yunnanensis in study area were obtained by SOC710VP, and hyperspectral features were analyzed to extract hyperspectral features parameters to build damage levels detection models and judgment rules.

Result With the aggravation of damage level of T. yunnanensis, the reflectance spectral curves of P. yunnanensis gradually declined at green bands (510-560 nm) and near-infrared bands (720-1 036 nm), and the peak values of spectral first derivative curves gradually decreased at red edge (680-760 nm). In 509-539, 549-564, 595-677, 687-692, 702-807, 838-875 nm, and 891-1 031 nm, the damage levels and reflectance and first derivative of P. yunnanensis needle were significantly correlated. Hyperspectral parameters S_Dr, D_y, (D-H)/(D+H), S_Dnir, and (S_Dnir-S_Dr)/(S_Dnir+S_Dr) were used to establish the monitoring models, the R² of measured value and predicted value all reached 0.9. The accuracy of quantitative judgment rules based on 4 monitoring models were higher than 80%, the rules (Healthy (< 1.589), Slight damage1.589, 2.465), Moderate damage2.465, 3.381), Severe damage (≥ 3.381)) based on multivariable linear regression model y=-7.720x₁+1.275x₂+1.251x₃-4.835x₄+1.135x₅+6.632, reached the highest precision (93.33%).

Conclusion The monitoring models and judgment rules based on hyperspectral feature parameters can monitor the damage level of T. yunnanensis effectively.