中文摘要：

由于大气吸收和散射等大气辐射传输影响，叶绿素荧光卫星遥感反演存在很大的困难和挑战。本文利用日本温室气体观测卫星GOSAT的TANSO-FTS超光谱数据，选取770 nm附近受大气影响较弱的KI夫琅和费暗线，借助KPNO2010高分辨率太阳辐照度光谱，设计了加权最小二乘拟合的叶绿素荧光卫星反演算法，利用矩阵的谱条件数确定了算法中KI吸收线所采用的权重系数，获得了中国区域2010年1月至2011年6月的叶绿素荧光数据。并利用TANSO-CAI云标识数据剔除了受云影响的反演结果，并按照2°×2°格网逐月计算了荧光强度均值。将反演叶绿素荧光强度结果与同期MODIS的增强性植被指数EVI、光合有效辐射比例FPAR、总初级生产力GPP产品作对比分析，结果表明：荧光强度高值主要分布在中国西南、中南等植被覆盖度高、生长旺盛的地区，荧光强度季节性变化规律与EVI、FPAR、GPP等相似，但季节变化比上述各参数变化提前且更敏感，可以反映其他参数所不具备的独特信息。

英文摘要：

Chlorophyll Fluorescence （ChlF） is an indicator of plant photosynthesis. Satellite remote sensing can detect the ChlF at the regional or global scale. However, this application of remote sensing is a relatively new technology. The influence of atmospheric transfer makes the retrieval of ChlF from satellite remote sensing data difficult. In this paper, the ultra-spectral data of Thermal and Near-infrared Sensor for carbon Observation-Fourier Transform Spectrometer （TANSO-FTS） on the Japanese Greenhouse gases Observing SATellite （GOSAT） and the KPNO2010 solar irradiance spectrum were selected. A weighted least square fitting algorithm to retrieve ChlF based on the potassium KI solar Fraunhofer line near 770 nm was presented. The spectral condition number of the coefficient matrix was used to determine the weight coefficient of spectral radiance at the KI line. The solar-induced ChlF signals were successfully retrieved from January 2010 to June 2011 in China. Cloudy data were masked based on the cloud flag data from the TANSO-Cloud and Aerosol Imager （TANSO-CAI）. The remaining ChlF data were averaged by 2-degree grids every month. ChlF emission in southwest and central-south China is relatively high owing to high vegetation coverage and vigorous photosynthesis. The retrieved ChlF were compared with EVI, FPAR, and GPP products of MODIS, which showed similar seasonal variations. However, the seasonal variation of ChlF was found to be more sensitive and occurs earlier. Thus, ChlF can provide unique information on vegetation photosynthesis. This study shows that spectral resolution of the ultra-spectral data of GOSAT is adequate for ChlF retrieval, but problems remain because of atmospheric transfer disturbance and spatial resolution.