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Crop Geometry Identification Based on Inversion of Semiempirical BRDF Models

文献类型： 外文期刊

作者： Zhao Chun-jiang 1 ; Huang Wen-jiang 1 ; Mu Xu-han 2 ; Wang Jin-di 2 ; Wang Ji-hua 1 ;

作者机构： 1.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

2.Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

关键词： Bidirectional reflectance distribution function (BRDF); Crop geometry; Sensitivity Analysis; Average leaf angle (ALA)

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2009 年 29 卷 9 期

页码：

收录情况： SCI

摘要： With the rapid development of remote sensing technology, the application of remote sensing has extended from single view angle to multi-view angles. It was studied for the qualitative and quantitative effect of average leaf angle (ALA) on crop canopy reflected spectrum. Effect of ALA on canopy reflected spectrum can not be ignored with inversion of leaf area index (LAI) and monitoring of crop growth condition by remote sensing technology. Investigations of the effect of erective and horizontal varieties were conducted by bidirectional canopy reflected spectrum and semiempirical bidirectional reflectance distribution function (BRDF) models. The sensitive analysis was done based on the weight for the volumetric kernel (f(vol)), the weight for the geometric kernel (f(geo)), and the weight for constant corresponding to isotropic reflectance (f(iso)) at red band (680 nm) and near infrared band (800 nm). By combining the weights of the red and near-infrared bands, the semiempirical models can obtain structural information by retrieving biophysical parameters from the physical BRDF model and a number of bidirectional observations. So, it will allow an on-site and non-sampling mode of crop ALA identification, which is useful for using remote sensing for crop growth monitoring and for improving the LAI inversion accuracy, and it will help the farmers in guiding the fertilizer and irrigation management in the farmland without a priori knowledge.

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