The radiosity-graphics model (RGM) is an important branch of computer simulation modelling for the vegetation bidirectional reflectance distribution function (BRDF). As the radiosity method is based on a global solving technique, the RGM can only deal with limited numbers of polygons, and has only been used for small-scale flat terrain scenes. However, the land surface is generally rugged, so it is necessary to extend the RGM to simulate the surface leaving radiance of the forest canopy at a large scale with complex topography. The methodology adopted in this paper is: (1) virtual forest scene generation combined with a digital elevation model; (2) scene division method, shadowing effect correction and multiple scattering calculation; (3) merging the simulated sub-scene bidirectional reflectance factors (BRFs) to get the whole-scene BRF. The paper compares this new method with other models by choosing a large-scale conifer forest scene with a GAUSS terrain from RAMI3 (http://rami-benchmark.jrc.it). Multi-angle imaging spectroradiometer (MISR) data are used to validate the extended RGM in a Picea crassifolia forest area at a satellite pixel scale in the field campaign in Gansu Province, China. The root mean square error and correlation coefficient between the simulated BRF and the MISR BRF are 0.018 and 0.98, respectively. The uncertainty and error sources of the large-scale RGM model are thoroughly analysed.