A strategy to integrate a priori knowledge for an improved inversion of the LAI from BRDF modelling
文献类型：SCI/SSCI论文
| 作者 | Yan G. J. ; Mu X. H. ; Ma Y. C. ; Li Z. L. |
| 发表日期 | 2008 |
| 关键词 | leaf-area index canopy reflectance vegetation indexes equifinality parameters retrieval algorithm limits modis misr |
| 英文摘要 | We propose a strategy to construct a priori knowledge in Bidirectional Reflectance Distribution Function (BRDF) model-based Leaf Area Index (LAI) inversion. In this strategy, the physical limitations, a best guess and its uncertainty for each parameter needed to be inverted were obtained from a spectral database. Vegetation index (VI) and growth date were used to provide more information about LAI. The relationship between LAI and VI was obtained by forward simulation using the BRDF model. The empirical model of the changing LAI and the growth date was obtained by statistical analysis of more than 600 field samples from a wheat paddock. A SAIL-reflectance model including the hotspot-effect (SAILH model) was used to generate bidirectional reflectance distribution. Gaussian distributed random noises were added on the reflectance as 'observation'. SAILH model was inverted to validate the effectiveness of this strategy. It was further validated using both of the ground measurements and airborne remote-sensing data. It is found that a priori knowledge is important for successful inversion, and our strategy is expected to yield more reasonable spatial and temporal LAI distribution. |
| 出处 | International Journal of Remote Sensing |
| 卷 | 29 |
| 期 | 17-18 |
| 页 | 4927-4941 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 0143-1161 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/22637]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Yan G. J.,Mu X. H.,Ma Y. C.,et al. A strategy to integrate a priori knowledge for an improved inversion of the LAI from BRDF modelling. 2008. |
入库方式： OAI收割
来源：地理科学与资源研究所
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