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Estimating Winter Wheat Nitrogen Vertical Distribution Based on Bidirectional Canopy Reflected Spectrum

文献类型： 外文期刊

作者： Yang Shao-yuan 1 ; Huang Wen-jiang 1 ; Liang Dong 2 ; Huang Lin-sheng 2 ; Yang Gui-jun 4 ; Zhang Dong-yan 2 ; Cai Shu- 1 ;

作者机构： 1.Chinese Acad Sci, Key Lab Digital Earth Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China

2.Anhui Univ, Minist Educ, Key Lab Intelligent Comp & Signal Proc, Hefei 230039, Peoples R China

3.Anhui Univ, Sch Elect & Informat Engn, Hefei 230039, Peoples R China

4.Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

5.Hebei Agr Tech Extens Stn, Shijiazhuang 050000, Peoples R C

关键词： Winter wheat;Nitrogen density;Canopy reflected spectrum;Bidirectional reflectance;Vertical distribution;Partial least-square (PLS)

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： 2015 年 35 卷 7 期

页码：

收录情况： SCI

摘要： The vertical distribution of crop nitrogen is increased with plant height, timely and non-damaging measurement of crop nitrogen vertical distribution is critical for the crop production and quality, improving fertilizer utilization and reducing environmental impact. The objective of this study was to discuss the method of estimating winter wheat nitrogen vertical distribution by exploring bidirectional reflectance distribution function (BRDF) data using partial least square (PLS) algorithm. The canopy reflectance at nadir, +/- 50 degrees and +/- 60 degrees; at nadir, +/- 30 degrees and +/- 40 degrees; and at nadir, +/- 20 degrees and +/- 30 degrees were selected to estimate foliage nitrogen density (FND) at upper layer, middle layer and bottom layer, respectively. Three PLS analysis models with FND as the dependent variable and vegetation indices at corresponding angles as the explicative variables were established. The impact of soil reflectance and the canopy non-photosynthetic materials was minimized by seven kinds of modifying vegetation indices with the ratio R-700/R-670. The estimated accuracy is significant raised at upper layer, middle layer and bottom layer in modeling experiment. Independent model verification selected the best three vegetation indices for further research. The research result showed that the modified Green normalized difference vegetation index (GNDVI) shows better performance than other vegetation indices at each layer, which means modified GNDVI could be used in estimating winter wheat nitrogen vertical distribution

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