生态学杂志2017，Vol.36Issue(4)：1150-1157,8.DOI:10.13292/j.1000-4890.201704.002
青海瑞香狼毒叶绿素含量高光谱预测模型
Hyperspectal predicting model of chlorophyll content of Stellera chamaejasme in Qinghai Province
摘要
Abstract
Chlorophyll content is an important indicator of plant growth.The chlorophyll content of Stellera chamaejasme can provide a basis for both monitoring the growth and controlling the hazard of S.chamaejasme.A typical degraded meadow,which was dominated by S.chamaejasme in Xinghai County,Qinghai Province,was chosen for the experiment.Five methods were adopted to predict,contrast and analyze the SPAD values so as to construct the optimal prediction model of the chlorophyll content of S.chamaejasme in Qinghai Province,which included partial least squares (PLS) in the whole wavelength region of 400-1000 nm,multiple linear regression (MLR) and PLS based on successive projections algorithm (SPA),the red edge parameters and vegetation index.Results indicated that the optimal prediction performance was achieved by SPAPLS model that was established by 9 characteristic wavelengths with SPA algorithm,and the correlation coefficient was predicted as 0.778,while the root mean square error was 1.895.Compared with the PLS model built on the full spectrum,the SPA-PLS model significantly reduced the computational complexity and improved the modeling efficiency.Compared with the SPA-MLR model,SPA-PLS model effectively solved the collinear problem among variables and also improved the forecasting accuracy,thus,it was the best model for predicting chlorophyll content of S.chamaejasme.Among predicting models built on the red edge parameters and vegetation index,a model constructed by MCARI index possessed the highest predicting accuracy with a correlation coefficient of 0.808 and a root mean square error of 1.969.Consequently,it could be the optimal vegetation index for inversing chlorophyll content of S.chamaejasme.关键词
狼毒/叶绿素含量/SPAD/回归模型/光谱参量Key words
Stellera chamaejasme/chlorophyll content/SPAD/regression model/spectral index引用本文复制引用
凯楠,刘咏梅,李京忠,常伟,谢小燕..青海瑞香狼毒叶绿素含量高光谱预测模型[J].生态学杂志,2017,36(4):1150-1157,8.基金项目
农业部公益性行业科研专项(201203062)和国家自然科学基金项目(41171225)资助. （201203062）
