Crop Geometry Identification Based on Inversion of Semiempirical BRDF Models
HUANG Wen-jiang1,3, WANG Jin-di2, MU Xi-han2, WANG Ji-hua1, LIU Liang-yun1, LIU Qiang3,NIU Zheng3
1. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China 2. Research Center for Remote Sensing and GIS, School of Geography, Beijing Normal University, Beijing 100875, China 3.The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China
Abstract：Investigations have been made on identification of erective and horizontal varieties by bidirectional canopy reflected spectrum and semi-empirical bidirectional reflectance distribution function(BRDF) models. The qualitative effect of leaf area index (LAI) and average leaf angle (ALA) on crop canopy reflected spectrum was studied. The structure parameter sensitive index (SPEI) based on the weight for the volumetric kernel (fvol), the weight for the geometric kernel (fgeo), and the weight for constant corresponding to isotropic reflectance (fiso), was defined in the present study for crop geometry identification. However, the weights associated with the kernels of semi-empirical BRDF model do not have a direct relationship with measurable biophysical parameters. Therefore, efforts have focused on trying to find the relation between these semi-empirical BRDF kernel weights and various vegetation structures. SPEI was proved to be more sensitive to identify crop geometry structures than structural scattering index (SSI) and normalized difference f-index (NDFI), SPEI could be used to distinguish erective and horizontal geometry varieties. So, it is feasible to identify horizontal and erective varieties of wheat by bidirectional canopy reflected spectrum.
Key words：Winter wheat;Crop geometry;Bidirectional reflectance distribution function (BRDF);Structure parameter sensitive index (SPEI)
黄文江1,3,王锦地2,穆西晗2,王纪华1,刘良云1,刘强3,牛铮3 . 基于核驱动模型参数反演的作物株型遥感识别[J]. 光谱学与光谱分析, 2007, 27(10): 1921-1924.
HUANG Wen-jiang1,3, WANG Jin-di2, MU Xi-han2, WANG Ji-hua1, LIU Liang-yun1, LIU Qiang3,NIU Zheng3. Crop Geometry Identification Based on Inversion of Semiempirical BRDF Models. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2007, 27(10): 1921-1924.
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