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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.
It is of great significance and prospect to monitor the canopy nitrogen status and productivity of wheat canopy using spatial remote sensing information.In this study, based on the information of wheat canopy reflectance spectra at different nitrogen levels, the response function was used to simulate the spectra constructed based on different satellite channels Index (including single-band, ratio spectral index and normalized spectral index), the quantitative relationship between the spectral index based on spaceborne channels and the nitrogen nutrition index of wheat canopy leaf was analyzed to determine the better nitrogen monitoring of wheat canopy leaf Satellite sensor and spectral band were used to establish the monitoring equation of nitrogen nutrition index in wheat canopy.The results showed that the leaf nitrogen (R2) was above 0.60. Prediction of wheat could be predicted using NDVI (PB4, PB2), NDVI (CH2, CH1), NDVI (MSS7, MSS5), RVI (MSS7, MSS5), MODIS1 and MODIS2 Leaf nitrogen uptake (LNA) was greater than 0.86. In comparison, NDVI (MSS7, MSS5) and NDVI (PB4, PB2) were the appropriate parameters for the prediction of LNA and LNA, respectively.