首页> 外文期刊>International journal of applied earth observation and geoinformation >Understanding the optical responses of leaf nitrogen in Mediterranean Holm oak (Quercus ilex) using field spectroscopy
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Understanding the optical responses of leaf nitrogen in Mediterranean Holm oak (Quercus ilex) using field spectroscopy

机译:使用场光谱法了解地中海霍姆栎(Quercus ilex)中叶氮的光学响应

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The direct estimation of nitrogen (N) in fresh vegetation is challenging due to its weak influence on leaf reflectance and the overlaps with absorption features of other compounds. Different empirical models relate in this work leaf nitrogen concentration ([N]Leaf) on Holm oak to leaf reflectance as well as derived spectral indices such as normalized difference indices (NDIs), the three bands indices (TBIs) and indices previously used to predict leaf N and chlorophyll. The models were calibrated and assessed their accuracy, robustness and the strength of relationship when other biochemicals were considered. Red edge was the spectral region most strongly correlated with [N]Leaf, whereas most of the published spectral indexes did not provide accurate estimations. NDIs and TBIs based models could achieve robust and acceptable accuracies (TBI_(1310.1720.730): R~2 =0.76, [0.64,0.86]; RMSE (%) = 9.36, [7.04,12.83]). These models sometimes included indices with bands close to absorption features of N bonds or nitrogenous compounds, but also of other biochemicals. Models were independently and inter-annually validated using the bootstrap method, which allowed discarding those models non-robust across different years. Partial correlation analysis revealed that spectral estimators did not strongly respond to [N]Leaf but to other leaf variables such as chlorophyll and water, even if bands close to absorption features of N bonds or compounds were present in the models.
机译:新鲜植被中氮(N)的直接估算具有挑战性,因为它对叶片反射率的影响较弱,并且与其他化合物的吸收特征重叠。在此工作中,不同的经验模型与霍尔姆橡树上的叶片氮浓度([N] Leaf)相关联,以反映叶片的反射率以及派生的光谱指数,例如归一化差异指数(NDI),三个波段指数(TBI)和先前用于预测的指数叶氮和叶绿素。当考虑其他生化试剂时,对模型进行校准并评估其准确性,鲁棒性和关联强度。红色边缘是与[N] Leaf密切相关的光谱区域,而大多数已发布的光谱指数未提供准确的估计。基于NDI和TBI的模型可以实现鲁棒且可接受的精度(TBI_(1310.1720.730):R〜2 = 0.76,[0.64,0.86]; RMSE(%)= 9.36,[7.04,12.83])。这些模型有时包括带有接近N键或含氮化合物以及其他生化物质吸收特征的带的指数。使用引导程序方法对模型进行独立且每年一次的验证,该方法可以丢弃在不同年份非稳健的那些模型。偏相关分析表明,即使模型中存在接近N键或化合物吸收特征的谱带,光谱估计量对[N]叶的响应也不强烈,但对其他叶变量(如叶绿素和水)的响应却很强。

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