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基于高光谱指数的塔里木河上游胡杨和灰叶胡杨叶片氮素含量估测

王家强1,伍维模1,2**,李志军1,2,温善菊1,牛建龙1,迟春明1   

  1. (1塔里木大学植物科学学院, 新疆阿拉尔 843300; 2新疆生产建设兵团塔里木盆地生物资源保护与利用重点实验室, 新疆阿拉尔 843300)
  • 出版日期:2014-10-10 发布日期:2014-10-10

Estimating leaf nitrogen content of Populus euphratica and P. pruinosa in the upper reaches of Tarim River using hyperspectral index.

WANG Jia-qiang1, WU Wei-mo1,2**, LI Zhi-jun1,2, WEN Shan-ju1, NIU Jian-long1, CHI Chun-ming1   

  1. (1Institute of Plant Science and Technology, Tarim University, Alar 843300, Xinjiang, China; 2Key Laboratory of Protection and Utilization of Biological Resources of Tarim Basin of Xinjiang Production & Construction Corps, Alar 843300, Xinjiang, China)
  • Online:2014-10-10 Published:2014-10-10

摘要:

采用高光谱技术,以胡杨、灰叶胡杨为实验材料,利用野外地物光谱辐射计获得了塔里木河上游胡杨、灰叶胡杨叶片的光谱反射率数据,同时进行叶片的采集并分析其氮素含量。结果表明:(1)以原始光谱反射率与叶片氮素含量的最大相关波段处的反射率为自变量,氮素含量为因变量,拟合的线性模型灰叶胡杨的决定系数大于胡杨,胡杨在657 nm处和灰叶胡杨689 nm处所构建的模型在叶片氮素预测模型中较为理想;(2)以光谱特征变量、植被指数及红边位置为自变量,叶片氮素含量为因变量所构建的线性模型拟合效果较好,其中叶片氮素与植被指数构建的模型其决定系数值较高,说明其具有较高的预测能力;(3)基于光谱面积的预测变量在监测叶片营养状况中也有较大的潜力。研究认为,利用高光谱反射率数据及其光谱变换参数来估测胡杨、灰叶胡杨的氮素含量是可行的。
 
 

关键词: 耕作方式, 水分利用效率, 光合特性, 干物质积累与分配, 籽粒产量

Abstract: Hyperspectral reflectances of Populus euphratica and P. pruinosa leaves were obtained using field spectrometer in the upper reaches of Tarim River. Leaf nitrogen content was also determined. The bands of 657 nm and 689 nm could be used as sensitive bands to estimate leaf nitrogen content of P. euphratica and P. pruinosa, respectively. The determination coefficient of the linear model between reflectance and leaf nitrogen content of P. euphratica was higher than that of P. pruinosa. Highly significant linear relationships were also found between leaf nitrogen content and hyperspectral characteristic variables, vegetation index and red edge position, respectively. The determination coefficients of linear models between leaf nitrogen content and vegetation index were higher than those of other models. Therefore, inversion models based on vegetation index have good predictability. Significant relationships also existed between leaf nitrogen content and spectral areas. Therefore, spectral areas also can be used to estimate leaf nitrogen content. It was feasible to estimate nitrogen content of P. euphratica and P. pruinosa leaves based on hyperspectral reflectance and parameters transformed from hyperspectral reflectance.

Key words: water use efficiency, grain yield, dry matter accumulation and allocation, tillage practices, photosynthetic characteristics