关键词: 盐胁迫, 气体交换参数, 叶绿素荧光, 生物量, 气孔特征

Abstract: Daxing’anling is a highly frequent forest fire disaster area in China. Accurate prediction of forest fuel moisture content is of great significance to improve the accuracy of forest fire forecast in this area. In this study, first derivative transformation and continuum removal methods were used to identify the bands sensitive to forest litter moisture. And the correlation coefficients were calculated between measured forest litter moisture and four spectral variables, including the original reflectance, the first derivative reflectance, the continuumremoval reflectance and first derivate of the continuumremoval reflectance. Then the highly relevant bands were selected as independent candidate variables and the forest litter moisture content estimation model was established by using a stepwise regression method. The determination coefficient (R²), mean relative error (MRE) and root mean square error (RMSE) of the model were calculated for evaluating the model. The results showed that there was a higher correlation between forest litter moisture content and first derivate of the continuumremoval reflectance compared to other spectral variables. The more sensitive bands were 398-668, 768-1068, 1098, 1278, 1388-1438, 1458-1538, 1868-1898, 1988-2088, 2198-2208, 2228-2238 nm (P<0.05). The extreme values of the correction coefficients were -0.653 and 0.610 at 2008  and 1888 nm, respectively. The model used to estimate forest litter moisture content was established by using multilinear stepwise regression method. The R², MRE and RMSE of the model were 0.537, 0.303 and 0.499, respectively. This study provides reference in fast estimating forest litter moisture content by using remote sensing technology.

Key words: stomatal trait, salt stress, chlorophyll fluorescence, biomass., gas exchange parameter