用冠层光谱比值指数反演条锈病胁迫下的小麦含水量  

Using Canopy Hyperspectral Ratio Index to Retrieve Relative Water Content of Wheat Under Yellow Rust Stress

作　　者：蒋金豹[1] 黄文江[2] 陈云浩[3] 

机构地区：[1]中国矿业大学(北京)地测学院,北京100083 [2]国家农业信息化工程技术研究中心,北京100097 [3]北京师范大学资源学院,北京100875

出　　处：《光谱学与光谱分析》2010年第7期1939-1943,共5页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(40701119);国家高技术研究发展计划项目(2007AA120205);国际科技合作计划项目(2007DFA20640);中央高校基本科研业务费专项资金项目资助

摘　　要：通过高光谱遥感估测条锈病胁迫下的小麦冠层水分含量。通过人工田间诱发不同等级小麦条锈病,在不同生育期测定感染不同严重程度条锈病的冬小麦冠层光谱、相对含水量(relative water content,RWC)以及调查小麦条锈病病情指数(disease index,DI)。研究发现随着小麦RWC的减少,冠层光谱反射率在近红外区域(900～1 300 nm)逐渐降低,而在短波红外区域(1 300～2 500 nm)逐渐增大,且RWC与DI间具有强负相关性。对冠层光谱进行平滑处理,利用冠层光谱近红外与短波红外水分敏感波段构建比值指数,然后建立以比值指数为变量的反演RWC线性模型,并分析对比各模型反演RWC的精度以及稳定性,结果发现比值指数R1 300/R1 200反演RWC的精度及稳定性(R2=0.63)都优于其他指数,其线性模型反演绝对误差为3.43,相对误差(relative error,RE)为4.78%。该研究结果不仅为判别小麦病害提供辅助信息,而且也为未来利用高光谱图像反演植物含水量提供理论与方法支持。The aim of this paper is to estimate canopy relative water contents （RWC） of winter wheat under yellow rust stress by using hyperspectral remote sensing. The canopy reflectance of winter wheat that infected different severity yellow rust was collected and the disease index （DI） of the wheat was investigated respectively in the fields, whereafter the wheat was sampled corresponding to the canopy reflectance measurements and the RWC of the whole wheat were measured in the Laboratory. The research showed that the canopy spectra reflectance gradually decreased in the near-infrared （NIR） region （900-1 300 nm） with RWC reduction, however, canopy spectra reflectance gradually increased in the short-wave-infrared （SWIR） region （1 300-2 500 nm）, and there was just higher minus correlation between RWC and DI. Smoothing the canopy spectra, the ratio indices were built by using the sensitive bands for water in NIR and SWIR, and then the estimation RWC linear models were built by using ratio indices as variables, and the model inversion precision and stability were analyzed and compared for estimation RWC. The result indicated that the inversion precision and the stability of the model with ratio index R1 a00/R1 200 as variable excel other models, the linear model＇s RMSE is 3.43, and the relative error is 4.78%. So, this study results not only can provide assistant information for diagnosing wheat disease but also can supply theories and methods for inversion vegetation RWC by using hyperspectral images in the future.

关 键 词：小麦 冠层光谱 条锈病 含水量 反演模型 

分 类 号：O657.3[理学—分析化学] S127[理学—化学]