| 光谱学与光谱分析 |
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| 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 |
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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.
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Received: 2006-06-08
Accepted: 2006-09-08
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Corresponding Authors:
HUANG Wen-jiang
E-mail: huangwj@nercita.org.cn
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| Cite this article: |
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HUANG Wen-jiang,WANG Jin-di,MU Xi-han, et al. Crop Geometry Identification Based on Inversion of Semiempirical BRDF Models[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2007, 27(10): 1921-1924.
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| URL: |
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https://www.gpxygpfx.com/EN/Y2007/V27/I10/1921 |
[1] HU Yan-ji,LAN Jin-hao(胡延吉, 兰进好). Chinese Journal of Agrometeorology(中国农业气象), 2001, 22(3): 28.
[2] Gerstl, S A W, Simmer C. Remote Sensing of Environment, 1986, 20: 1.
[3] Boegh E, Soegaard H, Broge N, et al. Remote Sensing of Environment, 2002, 81: 179.
[4] Wanner W, Strahler A H, Hu B, et al. Journal of Geophysical Research, 1997, 102: 17143.
[5] Gao F, Schaaf C B, Strahler A H, ert al. Remote Sensing of Environment, 2003, 86: 198.
[6] d’Entremont R P, Schaaf C B, et al. Journal of Geophysical Research, 1999, 104: 6229.
[7] HUANG Wen-jiang, WANG Ji-hua, LIU Liang-yun, et al(黄文江, 王纪华, 刘良云, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2005, 21(6): 82.
[8] ZHAO Li-li, ZHAO Long-lian, LI Jun-hui, et al(赵丽丽, 赵龙莲, 李军会, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2004, 24(1): 41. |
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