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于星载通道光谱指数与小麦冠层叶片氮素营养指标的定量关系

姚霞,刘小军,田永超,曹卫星,朱艳**,张羽   

  1. (南京农业大学/国家信息农业工程技术中心/江苏省信息农业高技术研究重点实验室, 南京 210095)
  • 出版日期:2013-02-18 发布日期:2013-02-18

Quantitative relationships between satellite channels-based spectral parameters and wheat canopy leaf nitrogen status.

YAO Xia, LIU Xiao-jun, TIAN Yong-chao, CAO Wei-xing, ZHU Yan, ZHANG Yu   

  1. (Jiangsu Province Key Laboratory for Information Agriculture, National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China)
  • Online:2013-02-18 Published:2013-02-18

摘要: 利用空间遥感信息大面积监测小麦冠层氮素营养状况和生产力指标具有重要意义和应用前景.本研究基于不同施氮水平下小麦冠层反射光谱信息,利用响应函数模拟基于不同卫星通道构建的光谱指数(包括单波段、比值光谱指数和归一化光谱指数),分析基于星载通道的光谱指数与小麦冠层叶片氮素营养指标的定量关系,确定监测小麦冠层叶片氮素营养的较好卫星传感器和光谱波段,建立小麦冠层氮素营养指标监测方程.结果表明:利用NDVI(MSS7, MSS5)、NDVI(RBV3, RBV2)、TM4、CH2、MODIS1和MODIS2遥感数据可以预估小麦叶片氮含量(LNC),其决定系数(R2)在0.60以上;应用NDVI(PB4, PB2)、NDVI(CH2, CH1)、NDVI(MSS7, MSS5)、RVI(MSS7, MSS5)、MODIS1和MODIS2可以预测小麦叶片氮积累量(LNA),其R2大于0.86.比较而言,NDVI(MSS7, MSS5)和NDVI(PB4, PB2)分别为预测小麦LNC和LNA的适宜星载通道光谱参数.

Abstract: Using spaceborne remote sensing information to monitor the crop canopy nitrogen status and crop productivity in a largescale is of great significance and application prospect in modern agriculture. With the hyperspectral reflectance data from the wheat canopy under different nitrogen fertilization levels, this paper constructed the spectral indices (including the single wavelength, ratio spectral index, and normalized difference spectral index) simulated by satellite channels, and established the nitrogen estimation equations by quantifying the relationships between the simulated channels spectral indices and the leaf nitrogen index. The results indicated that the spectral indices based on NDVI (MSS7, MSS5), NDVI (RBV3, RBV2), TM4, CH2, MODIS1,and MODIS2  could be reliably used for estimating the leaf nitrogen content (LNC), with R2 over 0.60, and the spectral indices based on NDVI (PB4, PB2, NDVI (CH2, CH1), NDVI (MSS7, MSS5), RVI (MSS7, MSS5), MODIS1, and MODIS2 could be accurately used for predicting the leaf nitrogen accumulation (LNA), with R2 greater than 0.86. Comparatively, NDVI (MSS7, MSS5) and NDVI (PB4, PB2) could be the more suitable spectral indices for predicting the wheat canopy LNC and LNA, respectively.