Multiangular remote sensing observation can provide more spatial structure information that make it possible to retrieve the 3 D structural parameters of vegetation. Currently

most of the inversion algorithms only use one single band in the field of multiangular remote sensing

the correlation between bands hasn’t been used efficiently for green vegetation. From the reflectance spectrum characteristic of green vegetation

we found that the basic shape of the spectrum can be used as prior knowledge in the inversion of vegetation structure. As a framework in this paper

spectral parameters were regenerated in the band of red

green and near infrared

their difference and ratio are used as the spectral prior knowledge in inversion. Through detailed simulation and inversion

it is clear from the statistical analysis that this method is more stable to observe noise than the single band based method which uses the averaged structural parameters inverted using one single band each time. It is also found that the inversion results tend to be closer to the ground truth than the single band based method after employing this kind of spectral prior knowledge.