光合有效辐射吸收比率（FPAR: Fraction of Absorbed Photosynthetically Active Radiation）是描述植被结构以及冠层-大气物质与能量交换过程的基本生理变量。并且作为全球气候观测系统（GCOS）以及陆地生态系统观测系统（GTOS）反映全球气候变化的关键气候参量之一。不仅是光能利用率模型、作物产量估算模型的重要输入参数之一，同时也是开展植被物候变化，作物生长监测，植被干旱预警以及土地覆盖变化的重要指示因子。因此，基于遥感的FPAR方法研究对于全球变化研究有着重要的意义。 本文基于能量平衡原理，结合非线性混合像元模型提出了简化的FPAR反演模型 FPEB。并用多地面实验数据对模型进行检验，分析模型的可行性与可靠性。将模型应用于遥感影像FPAR反演并与FPAR-NDVI统计模型反演的FPAR结果进行比较分析，同时也针对模型存在的问题，作了模型主要输入参数的敏感性分析。主要研究内容包括以下3个方面： 1、从能量守恒原理出发，结合非线性混合像元模型，分析了太阳入射能量中的植被冠层反射、土壤吸收分量的光谱反演方法，建立了简化的FPAR遥感反演模型（FPEB）。分别用2011年、2013年西藏自冶区那曲实验数据、2011年西藏自冶区当雄实验数据和2013年内蒙古自冶区海拉尔的实验数据，对论文建立的FPAR遥感反演模型进行了验证，并将FPEB模型反演结果与传统的植被指数统计模型反演结果进行了对比分析，结果表明论文中提出的FPEB模型的FPAR反演精度优于NDVI统计模型的反演精度，且与其它基于能量平衡原理提出的反演FPAR模型相比具有输入参数少，模型简单的优势，在空间区域和时间上具有很好的普适性。 2、开展了羌塘高原航空遥感试验与黑河流域生态-水文过程综合遥感观测联合试验（HIWATER）的遥感影像的FPEB模型FPAR反演实验，并将反演结果与用羌塘高原航空遥感试验地面数据（包括地面光谱数据与地面FPAR数据）建立的FPAR-NDVI统计模型反演的结果进行比较分析。实验结果表明FPEB模型反演FPAR的结果与FPAR-NDVI模型反演的结果具有很好的一致性而反演精度好于FPAR-NDVI统计模型反演的精度。 3、针对FPEB模型输入参数的不确定要素，选择了三个主要输入参数：植被覆盖度，太阳天顶角，植被冠层透过率，开展了模型的输入参数敏感性分析。结果表明，植被覆盖度对FPEB模型具有很大的敏感性；其次是太阳天顶角，随着太阳天顶角的升高其对FPEB模型的敏感性降低，当植被覆盖度达到60%时后，敏感性趋于饱和；植被冠层透过率具有较小的敏感性，变化趋势与太阳天顶角的敏感性趋势相同。

The fraction of absorbed photosynthetically active radiation (FPAR) is a physiological parameter describing the vegetation structure and the exchange of carbon and energy between vegetation canopy and atmosphere. It has been recognized as one of the essential climate variables for global climate change studies by the Global Terrestrial Observing System (GTOS) and the Global Climate Observing System (GCOS). It is not only considered as one important input in light use efficiency model and crop yield estimation model, it is also plays a key role in vegetation phenology detecting and crop condition monitoring. Thus, it is interesting for estimating FPAR using remote sensing and has important implications for global change research. In this paper, a simplified semi-empirical model of estimate FPAR base on principle of energy balance and non-linear mixing pixel model (FPEB) was presented firstly. It has been tested for analyzes its feasibility and reliability using the ground data of different independent experimental area. And the FPEB model also was compared with FPAR-NDVI statistic model then they are use to remote sensing. Through choosing the uncertainty factors, the sensitivity analysis is used to determine the influence of input parameters and variables to FPEB model. Specific research includes the following three aspects: 1.A method for retrieving vegetation canopy reflected and soil absorbed radiation components of incident PAR was analyzed using non-linear mixing pixel model, and a simplified semi-empirical model of estimate FPAR base on principle of energy balance (FPEB) was presented firstly. Then, the FPEB model were examined using four independent field at Nagqu district, Tibet Autonomous Region in 2011 and 2013, Dangxiong county, Tibet Autonomous Region in 2011 and Hailar district, Inner Mongolia Autonomous Region in 2013. And the FPEB model was also compared with to the traditional normalized difference vegetation index (NDVI) model. The results showed that the accuracy of FPEB model was better than NDVI-based model, and that the FPEB model was universal and valid for different regions or vegetation types. 2.Conduct avation remote sensing image FPAR inversion of airborne remote sensing experiment in Qiangtang Plateau and heihe watershed allied telemetry experimental research（HIWATER）, and the result was compared with the result of FPAR-NDVI model inversion FPAR, it was construted using the ground data of airborne remote sensing experiment in Qiangtang Plateau. The results show that the results of FPEB model inversiong FPAR and FPAR-NDVI model retrieving FPAR has perfacter consistency, but inversion accuracy of FPEB model is better than the inversion accuracy of FPAR-NDVI model. 3.Through choosing three uncertainty factors (solar zenith angle, vegetation canopy transmittance, vegetation coverage), the sensitivity analysis is used to determine the influence of input parameters and variables to FPEB model. Results showed that vegetation coverage is the important influence factot. Followed by solar zenith angle, with it increases, its sensitivity is reduces to FPEB model. Then sensitivity is beconing saturation when the values of vegetation coverage are lager than 80%. The sensitivity of vegetation anopy transmittance is low than solar zenith angle to FPEB model, its variation tendency is consistent with solar zenith angle.