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作 者:刘国顺[1] 李向阳[1] 刘大双[1] 喻奇伟[1]
机构地区:[1]河南农业大学国家烟草栽培生理生化研究基地,河南郑州450002
出 处:《生态学报》2007年第5期1763-1771,共9页Acta Ecologica Sinica
基 金:国家烟草专卖局重点资助项目(110200401021)~~
摘 要:综合多种烟草类型、品种及肥料处理因素,分析了17种光谱参数与烟草叶面积指数(LAI)、地上鲜生物重(AFW)、地上干生物重(ADW)的关系,建立逐步回归模型对烟草LAI、AFW、ADW进行估测并结合相关分析筛选出相应的特征变量。结果表明:5个回归方程的复确定系数R2、回归系数相伴概率均达到显著水平。包含17个光谱参量的逐步回归方程筛选出的第一自变量均为Rg/Rr,相关分析及散点图分析亦得出Rg/Rr与LAI、AFW、ADW相关系数分别为0.759、0.611、0.647,R2为0.576、0.3727、0.4184,均达到极显著水平,证明烟草LAI、AFW、ADW的特征变量为Rg/Rr。仅采用8种植被指数建立模型,证明利用比值植被指数(RVI)估测LAI、ADW亦是可行的。经过统计检验,建立的模型估测效果均较好,估测值与实测值的相关性均达到显著水平,其中包含特征变量Rg/Rr的回归模型估测效果优于RVI构建的模型。表明采用高分辨率光谱或宽波段光谱提取光谱变量可对烟草LAI、AFW、ADW进行监测,并可根据数据条件选择有效的估测模型,为烟草遥感数据分析提供方法。Leaf area index (LAI), aboveground fresh weight (AFW) and aboveground dry weight (ADW) are important parameters in monitoring of crop growth status. The tobacco stepwise regression models and characteristic variable were established by analysing the relationship between 17 spectral parameters and LAI, AFW, ADW in different type, breed, fertilizer treatments. The results showed that 5 regression equation R2 and coefficients reached 0.05 significant level. The first variable screened was Rg/Rr for the regression models of 17 spectral variables. The correlation coefficients of Rg/Rr and LAI, AFW, ADW were 0. 759,0. 611,0. 647, respectively and that of R^2 were 0. 576,0. 3727,0. 4184. They all reached 0.01 significant level. So Rg/Rr was the characteristic variable of LAI, AFW, ADW. Also, RVI could been used to estimate LAI,ADW by using the regression equation of 8 vegetation indexes. Through testing, all the models had good estimate effects, and regression models of Rg/Rr were better than those of RVI. This study indicates that it is feasible to monitor the tobacco growth by the characteristic parameters of hyperspectra and broadband spectra, and we can choose effective models based on the data, providing method of analysing remote sensing data.
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