植被生化组分光谱模型抗土壤背景能力分析

应用LOPEX'93(Leaf Optical Properties Experiment)数据,分析了统计回归模型在进行植被叶绿素和水分反演中抗土壤背景影响的能力,模型参数分别使用了:反射率及其变化形式、光谱位置变量、植被指数。在LOPEX'93数据库的植被波谱中分别加入10%-90%的实测土壤光谱信息,得到植被与土壤的混合光谱,并分析混合光谱对植被生化组分的响应。结果表明:应用反射率及其变化形式进行植被叶绿素反演时,以730nm和400nm组合的反射率和反射率倒数的对数为参数的模型具有最高的抗土壤背景能力,在土壤背景所占比例从低到高的变化过程中,以二者反射率组合为参数的模型与叶绿素的相关系数,始终保持在0.645附近,以二者反射率倒数的对数为参数的模型与植被叶绿素的相关系数保持在0.650附近;应用反射率及其变化形式进行植被含水量反演时,以1100,1170,1000,1040,1080nm组合的反射率为参数的模型以及以1170,960,1210,1090,1080,950,1220,1210nm反射率倒数的对数组合为参数的模型具有较高的稳定性,在土壤组分变化的过程中,以上模型与植被含水量的相关系数均稳定的高于0.99;对于光谱位置变量的分析中,以红边-绿峰-红谷组合的模型与植被叶绿素含量具有较高、而且稳定的相关系数,在土壤背景所占比例变化的情况下,相关系数稳定在0.53附近;在应用植被指数进行叶绿素的反演过程中,植被指数与叶绿素的相关系数在土壤背景所占比例变化的情况下变化较大,抗土壤背景的能力均较差;在应用植被指数进行植被水分含量的反演时,以水分指数Ratio975和Ratio1200相关系数最高,且在不同比例土壤背景变化下稳定,相关系数分别分布在0.980附近和0.960附近。该结果可用于指导不同植被覆盖条件下植被冠层参数的反演,提高反演的稳定性和准确性。

A Study on Anti-soil Background Capacity with Vegetation Biochemical Component Spectral Model

The main biochemical components of vegetations, such as chlorophyll and water, are directly involved in the major ecological processes and function of terrestrial ecosystem.Remote sensing of vegetation biochemical components may have important applications in the fields of agriculture and forestry. Many nonlinear or linear models have been developed for quantitatively retrieving vegetation biochemical components from satellite remotely sensed data. But it is often difficult to retrieve the biochemical components with satisfied accuracy, especially in sparsely vegetated areas because of the influence of the soil background. To select the better models that can resistance soil influence, in this paper, LOPEX'93(Leaf Optical Properties Experiment) dataset was used to analyze the anti-soil capacity of the spectral models in retrieving the vegetation chlorophyll and water content. The parameters used in the model include reflectance and its variants, spectral position variables and vegetation indices. The correlation coefficient between the vegetation biochemical component and the mixed spectra, which were produced by weighting vegetation spectra and the soil spectra with area ratio, has been analyzed. The results show that the models composed of the spectral parameters of the reflectance and its variants to inverse vegetation chlorophyll, the reflectance and the logarithm of reciprocal reflectance of 730 nm and 400 nm combination can keep a high correlation coefficient while the area ratio of soil component changes from 10 percent to 90 percent, the correlation coefficient between the reflectance and chlorophyll was around 0.645, and the correlation coefficient between the logarithm of reciprocal reflectance and chlorophyll was 0.650. To inverse water content, the combination of 1100 nm, 1170 nm, 1000 nm, 1040 nm, 1080 nm reflectance, and the combination of 1170 nm, 960 nm, 1210 nm,1090 nm, 1080 nm, 950 nm, 1220 nm, 1210 nm logarithm of reciprocal reflectance show a strong anti-soil capacity, the correlation coefficients between the two models and water content were all larger than 0.99. In the models composed of the spectral parameters of the spectral position variables, the parameter of red edge-green peak-red valley was selected as the strongest Anti-soil capacity parameter, the correlation coefficients were distributed around 0.530. In the models composed of the vegetation index to retrieve vegetation chlorophyll, the anti-soil capacity was poor but when the model is used to retrieve vegetation water content the correlation is stable though the soil area ratio is changable and the correlation coefficients are as high as 0.980 and 0.960 at the two typical water indices of Ratio 975 and Ratio1200, respectively. These conclusions can be used to guide the vegetation biochemical component inversion for sparsely vegetated regions.