In the present study, the authors built the relationships between the total chlorophyll and hyperspectral features of P. massoniana. The research results showed that (1) chlorophyll content has a good linear relationship with spectral reflectance around 527, 703, 1 364 and 1 640 nm, and this result is helpful for us to select some important bands when monitoring P. massoniana by remote sensing image; (2) all of the nine kinds of spectral feature parameters including red edge position, mean reflectance of red edge, mean reflectance around red edge position, red edge slope, red edge area, absorption depth of red band,green peak height, red edge normalized difference vegetation index and red edge vegetation stress index, have exponential function relationship (r=0.5-0.7) with the total chlorophyll; (3) the total chlorophyll content can be predicted by multivariate model by the nine spectral feature parameters, and partial least-squares regression model have higher prediction accuracy than the traditional multivariate linear model. The model’s root mean square (RMS) is 0.008 8, and mean absolute percentage error is 0.761 7%. During the growth of vegetation, biochemical parameters such as chlorophyll have vital function, for example, it can indicate the health status or pathological feature. So, the models mentioned just above will help us understand the ecological process of P. massoniana forest and provide valuable reference for monitoring P. massoniana and pine wood nematode disease by remote sensing technique.