XIE Dong-hui1, WANG Pei-juan2, QIN Wen-han3, et al. A Study on the Radiance Distribution in the Canopy Affected by Non-Lambert Characteristics of Leaf Based on RGM. [J]. Journal of Remote Sensing (6):868-874(2007)
XIE Dong-hui1, WANG Pei-juan2, QIN Wen-han3, et al. A Study on the Radiance Distribution in the Canopy Affected by Non-Lambert Characteristics of Leaf Based on RGM. [J]. Journal of Remote Sensing (6):868-874(2007) DOI: 10.11834/jrs.200706117.
A Study on the Radiance Distribution in the Canopy Affected by Non-Lambert Characteristics of Leaf Based on RGM
the Radiosity-Graphics combined Model(RGM) has many advantages in calculating the bidirectional reflectance factor(BRF).Because it takes advantage of radiosity theory and computer graphics technique
the model can contain much more detailed and complex structures of vegetation canopy and take reflection
transmission and multiple scattering into account
which is useful to understand the interaction between the light and the canopy.A hypothesis of Lambertian is made in the general radiosity theory
namely
all surfaces of components(i.e.
leaves
stem and background) in the scene are Lambert reflection/transmission.In fact
studies of the properties of leaves have shown that the bidirectional reflectance distribution functions(BRDF) of most leaves’ surfaces are not isotropic.In order to apply RGM to calculate the radiance distribution caused by the non-Lambert(specular) component
a semi-experimental Phong model is used to evaluate the specular radiosity from leaves’ surfaces.This method is applied to the maize canopy
and the results are analyzed.As an interesting experiment
this extended RGM
which includes diffuse and specular component at the same time
not only keeps the advantages of the general radiosity theory
but also eliminates the hypothesis of Lambertian in vegetation scene.
Key Laboratory of Arable Land Conservation in North China, Ministry of Agriculture and Rural Affairs, College of Land Science and Technology, China Agricultural University
Key Laboratory of Environmental Change and Natural Disaster, MOE, Faculty of Geographical Science, Beijing Normal University
Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences
School of Geographical Science, Northeast Normal University
College of Urban and Environmental Science, Changchun Normal University