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 a lgorithm 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 s easonal variations.However

the seasonal variation of ChlF was found to be more sensitive and occurs earlier.Thus

ChlF can p rovide unique information on vegetation photosynthesis.This study shows that spectral resolution of the ultra-spectral data of G OSAT is adequate for ChlF retrieval

but problems remain because of atmospheric transfer disturbance and spatial resolution.