中文摘要：

分析3个植被生化参数（叶绿素含量、叶片含水量和叶面积指数）对冠层光谱反射率变化的敏感程度以及影响波段区间，选择3个植被指数作为代价函数的优化比较对象，然后运用微粒群算法和PROSPECT＋SAIL模型分别反演叶绿素含量、叶片含水量和叶面积指数．结果表明：基于植被指数作为优化比较对象的模型反演效率较全波段方法有所提高；叶绿素含量、叶片含水量和叶面积指数反演值与实测值的复相关系数分别为90．8％、95．7％和99．7％，均方根误差分别为4．73μg·cm^-2、0．001g·cm^-2和0．08．采用植被指数作为优化比较对象可有效地提高基于PROSPECT＋SAIL模型反演植被生化参数的精度和效率．

英文摘要：

This study analyzed the sensitivities of three vegetation biochemical parameters / chloro- phyll content （ Cab）, leaf water content （ Cw）, and leaf area index （LAI） ] to the changes of canopy reflectance, with the effects of each parameter on the wavelength regions of canopy reflectance considered, and selected three vegetation indices as the optimization comparison targets of cost function. Then, the Cab, Cw, and LAI were estimated, based on the particle swarm optimization algorithm and PROSPECT＋SAIL model. The results showed that the retrieval efficiency with vegetation indices as the optimization comparison targets of cost function was better than that with all spectral reflectance. The correlation coefficients （R2） between the measured and estimated values of Cab, Cw, and LAI were 90.8 % , 95.7 % , and 99.7 % , and the root mean square errors of Cab, Cw, and LAI were 4.73 μg · cm^-2, 0.001 g · cm^-2 , and 0.08, respectively. It was suggested that to adopt vegetation indices as the optimization comparison targets of cost function could effectively improve the efficiency and precision of the retrieval of biochemical parameters based on PROSPECT＋ SAIL model.