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基于高光谱指数的林农复合系统小麦冠层氮含量估算研究(PDF)

《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

Issue:
2015年03期
Page:
91-95
Column:
研究论文
publishdate:
2015-05-30

Article Info:/Info

Title:
Research of the hyperspectral vegetation in deices for the estimation of the nitrogen content of wheat canopy in agro-forestry system
Article ID:
1000-2006(2015)03-0091-05
Author(s):
LIU Mindi12 XUE Jianhui12* CHU Jun12 HAO Lüyuan3 JIN Meijuan12
1. Co-Innovation Center for the Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China;
2. College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037,China;
3.School of Geography, Beijing Normal University, Beijing 100875,China
Keywords:
hyperspectral index nitrogen content of wheat leaves agro-forestry system
Classification number :
S718
DOI:
10.3969/j.issn.1000-2006.2015.03.017
Document Code:
A
Abstract:
This paper focused on the agro-forestry system, using FieldSpec Pro FR2500 for collecting 180 spectral data samples of wheat leaves from jointing stage to booting stage in the research,selecting nine hyperspectral vegetation indices from estimation model of monoculture crop canopy nitrogen content to estimate the nitrogen content of wheat canopy in agro-forestry system. Randomly selected 116 samples as the training set to establish estimation model based on nine indices, and the other 48 samples as the prediction set to establish estimation model for adaptive test of estimation model. The results showed that P-R2 of FN-NDNI reached to 0.839, 0.777 and C-R2 of SDr-SDb reached to 0.844, 0.758, which estimate the nitrogen content of wheat leaves in poplar-wheat intercropping ecosystem accurately, and the prediction accuracy of the remaining seven indices was not ideal. The prediction accuracy of the estimation model established by nine indices were all lower than in monoculture crop nitrogen content.

References

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Last Update: 2015-05-30