区域尺度冬小麦叶绿素含量的高光谱预测和空间变异研究

发布时间：2018-05-15 20:39

本文选题：冬小麦 + 叶绿素　；参考：《麦类作物学报》2017年07期

【摘要】：为从区域尺度探讨小麦SPAD的近地高光谱遥感监测技术,采用ASDField Spec 3.0型便携式高光谱仪获取的冬小麦冠层高光谱数据,利用相关分析和偏最小二乘法(PLSR)对SPAD进行建模预测,并采用地统计学方法进行空间变异制图。结果表明,冬小麦叶片SPAD值在不同生长阶段存在一定的差异,但在不同区域之间差异不显著。基于PLSR建立模型,并利用原始光谱和二阶导数光谱进行预测,R~2分别为0.653和0.995,均方根误差分别为2.622和0.327,相对析误差分别为1.549和13.66。综合来看,二阶导数光谱所建立的模型预测能力比原始光谱好。选择拔节期和成熟期进行区域化表达,与实测得到的SPAD空间分布图相比,采用全光谱数据和二阶导数光谱数据预测的SPAD均表现出了较高的空间相似性,其中二阶导数接近实测值。
[Abstract]:In order to study the near-ground hyperspectral remote sensing monitoring technology of wheat SPAD at regional scale, the hyperspectral data of winter wheat canopy obtained by ASDField Spec 3.0 portable hyperspectral instrument were used to model and predict SPAD by correlation analysis and partial least squares method. And geostatistical method was used to map spatial variation. The results showed that the SPAD values of winter wheat leaves were different in different growth stages, but there was no significant difference between different regions. The model was established based on PLSR, and the RR2 was predicted to be 0.653 and 0.995 by using the original spectrum and the second derivative spectrum, the root mean square error was 2.622 and 0.327, and the relative analysis error was 1.549 and 13.66 respectively. In a word, the prediction ability of the model based on the second derivative spectrum is better than that of the original spectrum. Compared with the measured SPAD spatial distribution map, the SPAD predicted by the full spectral data and the second derivative spectral data showed higher spatial similarity. The second derivative is close to the measured value.
【作者单位】：河南省农业科学院农业经济与信息研究所;
【基金】：国家自然科学基金项目(41601213) 高分辨率对地观测系统重大专项(09-Y30B03-9001-13/15) 河南省科技攻关重点项目(172102110090) 河南省农业科学院优秀青年基金项目(2016YQ21)
【分类号】：S127;S512.11

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