Objective To establish monitoring models and photosynthetic parameter simulation equations by measuring the hyperspectral data and photosynthetic data of Pinus yunnanensis, so as to effectively and quickly predict the damage period of Tomicus spp. and diagnose the health status of P. yunnanensis, and provide a reference for large-area application of hyperspectral remote sensing technology to achieve forest pest monitoring.

Method The damage caused by Tomicus spp. was investigated and the hyperspectral and photosynthetic data were obtained. The parameters which were significantly correlated with the damage period of Tomicus spp. were selected to establish monitoring models. The correlation between photosynthetic parameters and hyperspectral characteristic parameters was analyzed and the correlation equations of photosynthetic parameters were established.

Result As the hazard period prolonged, the spectral reflectance gradually decreases in the range of 740-1036 nm. "Red edge" and "blue shift" appeared in the first-order differential curve of the spectrum at 660-740 nm, and the peak value gradually decreased. The multivariate linear regression model which was established based on spectral characteristics showed the best fitting effect. The damage period of Tomicus spp. was closely correlated with Photo, and its cubic function model fitted well. The correlation between spectral index and photosynthetic parameters was established to obtain the optimal fitting equation of photosynthetic parameters.

Conclusion The models based on spectral index and photosynthetic parameters of P. yunnanensis can effectively monitor the hazard period of Tomicus spp. There is a significant correlation between the spectral index and photosynthetic parameters of P. yunnanensis, and a correlation model can be established to estimate the growth and health status of P. yunnanensis.