[Satellite remote sensing retrieval of canopy nitrogen nutritional status of apple trees at blossom stage].
Taking Qixia City of Shandong, China as the study area, and based on the Landsat-5 TM and ALOS AVNIR-2 images, the canopy retrieval reflectance of apple trees at blossom stage was acquired. In combining with the measured reflectance of sample trees, the nitrogen-sensitive spectral indices were constructed and selected. By using the sensitive spectral indices as the independent variables, the nitrogen retrieval models were established, and the model with the best accuracy was used for spatial retrieve. The correlations between the spectral indices and the nitrogen nutritional status were in the order of canopy > leaf > flower. The sensitive indices were mainly composed of green, red, and near infrared bands. The accuracy of the retrieval models was in the order of support vector regression > multi-variable stepwise regression > one-variable regression. The retrieval results based on different images were similar, and showed that the leaf nitrogen content was mainly of grades 3-4 (27-33 g x kg(-1)), and the canopy nitrogen nutrient indices were mainly of grades 2-4 (TM: 38-47 g x kg(-1); ALOS: 32-41 g x kg(-1)). The spatial distribution of the retrieval nitrogen nutritional status based on different images also showed the similar trend, i. e., the nitrogen nutritional status was higher in the north and south than that in the middle part of the study area, and the areas with the high grades of leaf nitrogen and canopy nitrogen were mainly located in Sujiadian Town and Songshan subdistrict in the northwest, Zangjiazhuang Town and Tingkou Town in the northeast, and Shewopo Town in the south, which were consistent with the distribution of the key towns for apple production in Qixia City. This study provided a feasible method for the acquisition of nitrogen nutritional status of apple trees on macroscopic scale, and also, provided reference for other similar remote sensing retrievals.
National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources/College of Resources and Environment, Shandong Agricultural University, Tai'an 271018, Shandong, China. lingwang@sdau.edu.cn
Ling
L
Wang
National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources/College of Resources and Environment, Shandong Agricultural University, Tai'an 271018, Shandong, China.
Geng-Xing
GX
Zhao
National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources/College of Resources and Environment, Shandong Agricultural University, Tai'an 271018, Shandong, China.
Xi-Cun
XC
Zhu
National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources/College of Resources and Environment, Shandong Agricultural University, Tai'an 271018, Shandong, China.
Rui-Yan
RY
Wang
National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources/College of Resources and Environment, Shandong Agricultural University, Tai'an 271018, Shandong, China.
Chun-Yan
CY
Chang
D002681:China; D017753:Ecosystem; D035264:Flowers / Q000254:growth & development; D027845:Malus / Q000254:growth & development* / Q000378:metabolism*; D009584:Nitrogen / Q000378:metabolism*; D058998:Remote Sensing Technology / Q000379:methods*; D017215:Satellite Communications; D013057:Spectrum Analysis / Q000379:methods
D009584:Nitrogen