基于光谱指数的冬小麦冠层叶绿素含量估算模型研究  

Estimation Model for Chlorophyll Content in Winter Wheat Canopy Based on Spectral Indices

作　　者：罗丹[1] 常庆瑞[1] 齐雁冰[1] 李媛媛[1] 李松[1] 

机构地区：[1]西北农林科技大学资源环境学院,陕西杨凌712100

出　　处：《麦类作物学报》2016年第9期1225-1233,共9页Journal of Triticeae Crops

基　　金：国家高新技术研究发展计划(863计划)项目(2013AA102401);教育部高等学校博士学科点专项科研基金项目(20120204110013)

摘　　要：为探索对冬小麦冠层叶绿素含量反应敏感的高光谱波段组合，同时比较不同光谱指数对小麦冠层叶绿素含量的估测效果，通过分析350-2500nm波段范围内原始光谱反射率及其一阶导数光谱的任意两两波段交叉组合而成的主要高光谱指数与冬小麦冠层叶片叶绿素含量的定量关系，建立冬小麦冠层叶绿素含量估算模型。结果表明，选用归一化光谱指数（NDSI）、比值光谱指数（RSI）、差值光谱指数（DSI）和土壤调节光谱指数（SASI）建立的冬小麦冠层叶绿素含量监测模型决定系数均大于0．71，标准误差均小于1．842。利用独立试验资料进行检验，表现最好的是RSI（FD689，FD609）和SASI（R491，R666）L=0.01，预测精度高达98．2％，模型精确度和可靠性较高。The objective of the present research was to estimate the winter wheat canopy chlorophyll content by using hyperspectral technology, which can indicate the plant healthy status in real time and non-destructively. The quantitative relationship was established between the winter wheat canopy chlorophyll content and major hyperspectral indices calculated by combining any two wavebands with original reflectance and its derivative within the full spectral range of 350-2 500 nm. Four kinds of spectral indices were studied in this paper-Normalized Difference Spectral Index（NDSI）, Ratio Spectral Index（RSI）, Difference Spectral Index（DSI）, Soil Adjust Spectral Index（SASI）. The results showed that the monitor models based on these spectral indices to estimate chlorophyll content in win- ter wheat canopy gave the correlation coefficient no less than 0.71 and RMSE lower than 1. 842. Testing of the regression equation with independent experiment data produced that the prediction accuracies was reached above 98. 2%, with the best performance from the model for chlorophyll content predication in winter wfieat canopy based on RSI（FD689 ,FD609 ） and SASI（R491 , R666）L=0.01. The results suggested that it is feasible to use hyperspectral indices for the measurement of chlorophyll content more rapidly and accurately in winter wheat canopy.

关 键 词：冬小麦 叶绿素 光谱指数 估算模型 

分 类 号：S512.1[农业科学—作物学] S313