Abstract: Dendrolimus tabulaeformis has caused serious damage to Pinus tabuliformis. According to the statistics, there are 0.12 million hectares of destroyed area in Liaoning Province of northeastern China every year, and the direct economic loss is 3.4 million CNY per year. The application of remote sensing technology, especially hyperspectral remote sensing to pest monitoring is one of the future directions of forestry pest monitoring. Hyperspectral remote sensing technology can provide a simple,effective and non-destructive data acquisition,which can offer processing method for quantifying diagnosis plant chlorophyll content and moisture content as well. This study uses the field portable spectrometer to measure the reflectance spectrum of trees with different leaf loss rates, uses the spectrophotometer to measure leaf chlorophyll content and measures the leaf moisture content with drying method. To calculate the linear relationship between normalization spectrum index (NDSI), ratio spectrum index (RSI), differential spectrum index (DSI) and chlorophyll a content, chlorophyll b content, moisture content, the spectrum index with maximum value of linear relationship was the key spectrum index. This study constructs regression model between the key spectrum indexes and the leaf loss rate, selects the spectrum index jet including DSI(808,816), RSI(482,494), NDSI(881,920), NDSI(907,919) with the stepwise regression algorithm, and builds the regression equation y=1.781 8－3.172 4×NDSI(808,816)－0.960 6×RSI(482,494)－2.196 7×NDSI(881,920)－1.241 9×NDSI(907,919) , whose R2 was 0.786. The root mean square error (RMSE) was 0.089 and relative error (RE) was 11.7%, which shows that this model is good and can be used to estimate the degree of leaf loss rate of P. tabuliformis. This model will help to make comprehensive analysis of the victimization degree of P. tabuliformis and improve the accuracy of pest monitoring degree, and overcome the sidedness and limitation of using single indicator of chlorophyll or moisture content.