Abstract: Abstract: GF-1 satellite was launched in April 2013. Since then various researches and operations using the GF-1 imagery have been conducted. This study tries to establish the inversion model for the biophysical variable photosynthetically active radiation (PAR) derived from GF-1 imagery. The inversion of the variable aerosol optical depth (AOD) is first carried out using the surface reflectance product of MODIS (moderate-resolution imaging spectroradiometer) (it is MOD09A1). Based on the typical ground-object spectral library data provided by the United States Geological Survey (USGS), and spectral response function of the GF-1/WFV sensors, the study has found that the difference in terms of the blue band surface reflectance generated by 2 sensors of GF-1/WFV and MODIS is very small. MODIS data can thus be assimilated to create GF-1 surface reflectance library. The second simulation of satellite signal in the solar spectrum (6S) atmospheric radiation transfer model is applied to produce an atmospheric parameter look-up table (LUT). By comparing solar incident irradiance at top of atmosphere (TOA) and radiation brightness value at the entrance pupil of the sensor, and using surface reflectance product from MODIS, the authors have achieved the ground-air decoupling and the inversion of AOD. After establishing AOD library, the atmospheric parameters such as atmospheric transmittance, atmospheric hemisphere albedo, and atmospheric diffuse transmittance are computed and interpolated to LUT. Combined with the calculation of sun incident radiation intensity, the ground solar radiation intensities at red, green and blue bands of GF-1 are produced. By analyzing the relationship between the ground solar radiation intensities and overall 400-700 nm PAR values provided by MOD09A1, 3 conversion coefficients are computed. The coefficients have the values of 0.09156, 0.09951, and 0.1007 respectively for the blue, green and red bands, realizing the inversion from the ground solar radiation intensity of 3 discrete wavebands to PAR. By selecting Yucheng region, Shandong Province as a study area, and using 13 GF-1 images registered from January to December in 2014, the authors generated the values of PAR for the study region and conducted the accuracy assessment for the inversion using the ground measured values of PAR. The results show that the PAR acquired by the inversion approach described in this paper has an overall accuracy of 92.63%, with an averaged absolute value of error of 14.56 W/m2 and an averaged relative error of 7.37%. Study shows that GF-1 data can be effectively applied for the inversion of PAR; the establishment of reflectance library is feasible by including MOD09A product, and generating LUT through the 6S model. Finally this PAR inversion approach can provide reliable data support for crop growth monitoring, and parameter estimation based on GF-1 imagery.