Estimating nitrogen content based on hyperspectrum of the apple florescence canopy
The paper is to establish a kind of fast, nondestructive method of estimating nitrogen content for the apple canopy and to provide the prior knowledge for large area of fruit trees nutrition diagnosis with remote sensing technique.Utilizing detection hyperspectral data of the apple florescence canopy and nitrogen content data in Qixia and MengYin counties of experimental orchards in two years.The correlation analysis of hyperspectral reflectance and its eleven transforms with nitrogen content is proceed, the bigger correlation coefficient as independent variable, nitrogen content as dependent variable.The estimating model of nitrogen content is established by multiple stepwise regression analysis.The model is inspected by the data of 2008 and verified by the data of 2009.The results showed that the correlation is less to the original spectral reflectance (R) and its reciprocal(1/R), logarithmic (lgR), square root (R1/2) and the content of nitrogen ,but it is enhanced obvious in their first derivative, second order derivatives and nitrogen content.Estimating model of nitrogen content is built.The best model for the independent variable (lgR) is Y =31.621-2732.6096 X832-3307.728 X849 + 2901.7231 X922-3172.324 X1019 after optimization.Upon testing, the best model of the estimated value and measured value, which the correlation factor of fitting equation R2 is the largest, 0.7325, the total root mean square difference RMSE is minimum, 2.3802, the relative error RE % is minimum, 8.1% and estimation accuracy is reached to 91.9%.The best estimating model validation shown that two experimental validation precision are achieved 80% above.It shown that this model used for apple florescence canopy of nitrogen content in the estimation is very stability and universality.
Apple florescence Hyperspectrum of canopy Nitrogen content Estimation
Zhu Xicun Jiang Yuanmao Zhao Gengxing Li Haiyan Wang Ling
College of Resources and Environment,Shandong Agricultural University,Tai”an 271018,China;College of College of Horticulture Science and Engineering,Shandong Agricultural University,Tai”an 271018,China College of Resources and Environment,Shandong Agricultural University,Tai”an 271018,China College of Resources and Environment,Shandong Agricultural University,Tai”an 271018,China;Key Labora
国内会议
2012年精准农业与农业空间信息技术学术交流暨农业信息化智能化科技成果推介会
西安
英文
148-159
2012-07-22（万方平台首次上网日期，不代表论文的发表时间）