文章提出了利用遥感光谱数据反演小麦冠层氮素垂直分布的化学计量学方法,运用偏最小二乘算法(PLS),穷尽测定的小麦田间冠层可见光和近红外光谱不同波长处的冠层光谱反射率及其组合与小麦不同层次的叶绿素、叶片全氮含量之间的关系。通过2001~2002年的建模和2003~2004年的验证试验,求得了用PLS算法对叶片全氮上层、中层、下层垂直分布估算结果的相关性。表明PLS算法能够用于反演作物冠层生物化学参数的垂直分布。运用PLS的小麦氮素垂直分布的估算方法,较以往单一冠层估算方法精度明显提高,对于生产上迫切需求对作物中、下层叶片氮素状况的监测来指导适时和适量施肥具有指导意义。
With the widespread application of remote sensing (RS) in agriculture, monitoring and prediction of crop nutrition condition attracts attention of many scientists. Foliar nitrogen content (N) is one of the most important nutrients for plant growth, and vertical leaf N gradient is an important indicator of crop nutrition situation. Investigations have been made on N vertical distribution to describe the growth status of winter wheat. Results indicate that from the canopy top to the ground sudace, N shows an obvious gradient decreasing trend. The objective of this study was to discuss the inversion method of N vertical distribution with canopy reflected spectrum by the partial least squares regression (PLS) method. PLS was selected for the inversion of upper, middle and lower layers of N. To improve the accuracy of prediction, the N in the upper layer as well as in the middle and bottom layers should be taken into consideration when crop nutrition condition is appraised by RS data. The established models by the observed data in year 2001-2002 were validated by the data in year 2003-2004. The inversion precision and error were acceptable. It provided a theoretic basis for widely and non-damaged variable rate nitrogen application of winter wheat by canopy reflected spectrum.