山东农业科学2012，Vol.44Issue(3)：7-12,16,7.
基于高光谱遥感的花生叶片氮积累量监测模型的研究
Study on Monitoring Model for Nitrogen Accumulation in Peanut (Arachis Hypogasa L.) Leaves Based on Hyper- Spectral Remote Sensing
摘要
Abstract
Nitrogen condition of crops was an important indicator for evaluating growth vigor, increasing yield and improving quality, so it was significant of real - time and lossless estimation of nitrogen accumulation in leaves for nitrogen management during crop production. In this study, the peanut variety Fenghua 1 with large seed was used as experimental material to study the relationship between nitrogen accumulation in peanut leaves and canopy hyper - spectral remote sensing parameters under field conditions. The results were as follows. The nitrogen content decreased gradually in peanut leaves with the growth process, and there were little differences between different treatments. The variation trend of nitrogen was a single peak showing that the nitrogen content increased firstly and then declined, and reached the peak at the pod - setting stage. The canopy spectrum reflectance of peanut increased with the increase of nitrogen accumulation in the wave band of 740 ~ 1 100 nm, and the sensitive bands to nitrogen accumulation were mainly present in near - infrared and visibleranges, in which, the red edge area showed the most significant The regression relationship of hyper - spectral parameters with nitrogen accumulation was analyzed through construction of multiple vegetation indices by techniques such as differential. The results showed that the means of amplitude of red edge (Dr) , nitrogen reflectance index (NRI) and normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) related most closely with the nitrogen accumulation with the determination coefficients of 0.9194, 0.8984, 0. 8918, 0. 8899, 0. 8794 and 0. 8797 respectively. The test results conducted by another group of independent data indicated that the two parameters of red edge position (RFP) and Dr could predict nitrogen accumulation the best with the RMSE as 1.78 and 1. 10 and the relative error as 5. 29% and 3. 59% respectively. The RMSE of NDVI and SAVI was 1. 15 and 1. 19 with the relative error as 5.42% and 7.41% respectively. In a word, the model constructed with Dr as the independent variable could evaluate the status of nitrogen accumulation well.关键词
花生/高光谱遥感/叶片氮积累量/监测模型Key words
Peanut (Arachis hypogasa L ) / Hyper - spectral remote sensing/ Nitrogen accumulation in leaves/ Monitoring model分类
农业科技引用本文复制引用
张晓艳,王丽丽,刘锋,封文杰,刘淑云,朱建华..基于高光谱遥感的花生叶片氮积累量监测模型的研究[J].山东农业科学,2012,44(3):7-12,16,7.基金项目
国家科技支撑计划项目(2006BAD21B04-20)资助. （2006BAD21B04-20）
