Model for predicting the nitrogen content of rice at panicle initiation stage using data from airborne hyperspectral remote sensing
Model for predicting the nitrogen content of rice at panicle initiation stage using data from airborne hyperspectral remote sensing
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DOI：
10.1016/j.biosystemseng.2009.09.002
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发表时间：
2009-12-01
影响因子：
5.1
通讯作者：
Umeda, Mikio
中科院分区：
文献类型：
--
作者：
Ryu, Chanseok;Suguri, Masahiko;Umeda, Mikio
利用航空高光谱遥感数据，建立了一个通用的水稻幼穗分化期氮素含量预测模型。植被数据之间存在显着差异，这取决于天气条件下从土壤中吸收氮的影响。因此，一年的反射率值可能会表现出不同的趋势，由于缺乏植被。当偏最小二乘回归（PLSR）模型估计使用的所有组合的三年数据，从2005年的数据，相关系数（r）大于0.758，和根均方误差（RMSE）的预测的全交叉验证小于0.876 g m（-2）。2003-2004-2005年的模型的准确性确定使用五个潜变量（PC），与r = 0.938和RMSEP = 0.774 g m（-2）。有两种不同的模式与近红外或红边区域的回归系数。当2003-2004年模型使用2005年的数据进行验证时，PLSR模型的预测误差为1.050 g m（-2）。使用2004年的数据，2003-2005年的模型为2.378 g m（-2），使用2003年的数据，2004-2005年的模型为5.061 g m（-2）。2003-2004年模型和2003-2004-2005年模型之间的每个潜变量都有相似之处和差异。2003-2004-2005年模式可能更适合用作通用模式，因为它可以考虑和验证所有三年的数据。(C)2009年IAgRE。由爱思唯尔有限公司出版。保留所有权利。
Airborne hyperspectral remote sensing was used to provide data for a general-purpose model for predicting the nitrogen content of rice at panicle initiation stage using three years of data. There were significant differences between the vegetation data which were affected by the uptake of nitrogen from the soil depending on weather conditions. Therefore, the reflectance values obtained for one year may exhibit a different trend, due to the lack of vegetation. When the partial least squares regression (PLSR) models were estimated using all combinations of the three-year data, except for the model incorporating the data from 2005, correlation coefficients (r) were greater than 0.758, and the root mean squared error (RMSE) of prediction of the full-cross validation was less than 0.876 g m(-2). The accuracy of the 2003-2004-2005 model was determined using five latent variables (PCs), with r = 0.938 and RMSEP = 0.774 g m(-2). There were two different patterns for the regression coefficients associated with the NIR or red-edge regions. When the 2003-2004 model was validated using the data from 2005, the prediction error of the PLSR model was 1.050 g m(-2). This became 2.378 g m(-2) for the 2003-2005 model using the data from 2004 and 5.061 g m(-2) for the 2004-2005 model with the data from 2003. There were similarities and differences for each latent variable between the 2003-2004 model and the 2003-2004-2005 model. The 2003-2004-2005 model might be more suitable for use as a general-purpose model, because it is possible to consider and validate all of the three years data. (C) 2009 IAgrE. Published by Elsevier Ltd. All rights reserved.