Abstract:

In the research of quantitative remote sensing, bidirectional reflectance distribution function (BRDF) of the Earth surface are important to understand the course and mechanism of the interaction between light and vegetation. And according to the principles of the BRDF models, physical models of vegetation in the field of remote sensing can be divided into three categories: geometry optical models (GO), radiance transfer models (RT) and computer simulation model. The computer simulation models, for instance, Monte Carlo, ray-tracing and radiosity, are paid more attention with the development of computer technology. The radiosity method is a powerful tool to describe the reflectance distribution from the canopies, which can take much more detailed structures of vegetations and the course of reflectance, transmittance and multiple-reflectance between the components in the scenes into account and help to understand and simulate the radiation distribution of canopies.
In this study, summer corn was selected as an example and light distributions in the canopy were simulated with RGM (radiosity-graphics combined model). First, three dimensional structures of corns were rendered with the modified extended L-systems (MELS) method using the statistical parameters measured in the field at Luancheng ecosystem station of Chinese academy of science, located at Hebei Province in 2000（Longitude: 37º52´N，latitude: 114º39´E，altitude: 50.5 m）. Second, RGM, which can take much more detailed structures of vegetation canopies into account, was analyzed and applied to simulate the radiance distribution in the corn canopy. Finally, results of BRF simulated by RGM model were compared with those measured data in the field. They were both agreed well. Therefore, BRF simulated by the model can be used to supply the spectrum database or to supplement measured data. The intermediate result of simulation can also be use to analyze APAR in the canopy as well.

Key words: RGM(Radiosity-graphics combined model), BRF(bidirectional reflectance factor), MELS, Corn