农机化研究2016，Vol.38Issue(6)：210-214,5.
基于高光谱的甜菜冠层氮素遥感估算研究
Models of Estimating Sugar Beet Nitrogen Using Hyperspectral
摘要
Abstract
This paper analyzes the beet canopy spectra under four pretreatment were used partial least squares regression ( PLSR) and principal component regression ( PCR) to establish beet nitrogen content estimation model , compare differ-ent methods of pretreatment and different regression estimation accuracy impact on PLSR , the first order derivative of the spectral data processing model established best accuracy ( RMSE=2.34g/kg, RE=19.6%), smoothing, estimation model followed by MSC and SNV established;for PCR toHe said precision spectral data smoothing model established best (RMSE=2.34g/kg,RE=19.4%).Overall, there are some different pre-treatment model to estimate the accuracy of differences , but the two regression PLSR and PCR methods to estimate the nitrogen content of beet little effect model .关键词
甜菜冠层/氮素/估算/光谱预处理/植被指数/最小二乘法/主成分回归Key words
sugar beet/Nitrogen/estimate/principal component regression/spectral preprocessing/vegetation index/least square分类
农业科技引用本文复制引用
李哲,田海清,王辉,徐琳,李斐,史树德..基于高光谱的甜菜冠层氮素遥感估算研究[J].农机化研究,2016,38(6):210-214,5.基金项目
国家自然科学基金项目(41261084) （41261084）
国家现代农业产业技术体系专项基金( CARS-210402) （ CARS-210402）
