首页> 外文会议>International Symposium on Intelligent Information Technology in Agriculture(ISIITA) >THE VERTICAL NITROGEN DISTRIBUTION IN CANOPY AND ITS SPECTRAL RESPONSE IN WINTER WHEAT
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THE VERTICAL NITROGEN DISTRIBUTION IN CANOPY AND ITS SPECTRAL RESPONSE IN WINTER WHEAT

机译:冬小麦冠层垂直氮气分布及其光谱响应

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The precision of quantificational remote sensing (RS) can be improved by tapping the potential of sensor, transferring model and exactly describing of the object. We think exactly describe the object is the base of improving inversion accuracy of RS. For this purpose, the vertical distribution of leaf nitrogen (N) concentration and Chl (a + b) content in canopy and their spectral response in winter wheat were investigated. Apparent descending trend of leaf N from the upper layer to the lower layer were found. At early stage, there were stable N gradient between different layers. Greater N gradient emerged at middle and latter growth stage and the gradient sharpened with the N application amount. The vertical distribution of Chl (a + b) was similar to that of N. But there were greater gradient of Chl (a + b) concentration than that of N content between upper and middle layer and less between middle and lower layer. The amount of N application decreased the Chl ( a + b) gradient between middle and lower layer, which differ from that of leaf N gradient. Under lower N condition, there existed significant spectral reflectance difference among different layers at the red wavebands, from 1400 nm to 1800 nm and from 1950 nm to 2300 nm. And, the spectral reflectance of lower layer was significantly higher than that of upper and middle layer. But the amount of N application didn't affect the characteristics of spectral reflectance for leaf in different layers. Besides, the correlative coefficients between canopy spectral reflectance and foliar biochemical contents of different layers were analyzed. The spectral reflectance was significantly correlated with foliar Chl (a + b) content of middle and lower layers. We thought the inversion accuracy of RS could be improved by using layer information. Future work should involve giving more attention on the method for multi-angle analyzing and establishing inversion model.
机译:通过点击传感器的电位,传输模型和精确描述对象,可以改善量化遥感(RS)的精度。我们认为究竟描述了对象是提高rs的反演精度的基础。为此目的,研究了冬小麦冠层中叶片(N)浓度和CHL(A + B)含量的垂直分布及其光谱反应。发现了从上层到下层的叶片n的表观下降趋势。在早期,在不同层之间存在稳定的N梯度。在中间增长阶段出现的较大N梯度,梯度与N施用量锐化。 CHL(A + B)的垂直分布类似于N的垂直分布。但是,在上层和中间层之间的N含量的CHL(A + B)浓度具有更大的梯度,并且在中下层之间较少。 N申请的量减少了中下层之间的CHL(A + B)梯度,其与叶N梯度的梯度不同。在较低的N条件下,红波带的不同层之间存在显着的光谱反射率差,从1400nm到1800nm和1950nm到2300nm。并且,下层的光谱反射率明显高于上层和中间层。但是N申请的量并不影响不同层叶片光谱反射率的特征。此外,分析了层内光谱反射率和不同层的叶面生化含量之间的相关系数。光谱反射率与中下层的叶酸CHL(A + B)含量显着相关。我们认为通过使用层信息可以改善RS的反转精度。未来的工作应涉及更加关注多角度分析和建立反演模型的方法。

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