基于现场光谱的翅碱蓬生物量遥感反演方法研究

Research on Remote Sensing Inversion Biomass Method Based on the Suaeda Salsa’s Measured Spectrum

利用便携式地物光谱仪和植被冠层分析仪测定辽东湾双台河口盐沼植被翅碱蓬的光谱数据和叶面积指数(LAI),建立翅碱蓬光谱反射率曲线;探讨翅碱蓬的植被指数与叶面积指数和生物量的相关关系,得到以下结论:(1)9月底翅碱蓬在630nm红光波长出现明显的反射峰值,反射率达到了12%～15%,在680～700nm,有明显的"红谷"形态,在760nm左右有明显的"红边",反射率达到25%～30%。(2)翅碱蓬植被指数及叶面积指数的回归分析中,SAVI和MSAVI指数与LAI的相关关系较其他指数好,最高的R2值达到0.711。对比不同指数的Linear回归方程发现,SAVI和MSAVI指数与LAI的相关关系R2值达到0.696,0.695;其次为RVI值0.664,NDVI值0.649及PVI值0.466。(3)翅碱蓬生物量(Biomass)与PVI,SAVI和MSAVI的相关系数R2较高,直线回归方程相关系数分别达到0.626,0.698和0.679;对数方程相关系数为0.592,0.706和0.683;二次方程相关系数分别为0.688,0.711和0.683。

Suaeda salsa is one of characteristic vegetation of wetlands in Northern China. By measuring the spectral data and leaf area index （LAI） of the Suaeda salsa in the ShuangTai Estuary of Liaodong Bay by the use of portable spectrometer and vegetation canopy analyzer, collecting the biomass of the Suaeda salsa samples, setting up the spectral reflectance curve of the Suaeda salsa, probing into the relationship between the vegetation index and the leaf area index of the Suaeda salsa, carrying out regression analysis of LAI and biomass and constructing the function equation, some conclusion were drawn： （1） By the end of September the spectral characteristics of Suaeda salsa show that at the red band 630 nm there is a clear reflection of the peak with a reflection rate of 12%-15%; there is a clear ＂red valley＂ configuration between 680 and 700 nm, and there is a clear ＂red edge＂ reflection rate of 25%-30% about 760 nm. （2） It was found that there is best correlation between vegetation index （SAVI and MSAVI） and LAI compared to other vegetation index in the regression analysis of the LAI and vegetation index. The correlation coefficient R^2 is 0.711. By comparison of vegetation index linear regression equations, the correlation coefficient （SAVI and LAI） R^2 is 0.696; the value of R^2 （LAI and MSAV） is 0.695; the value of R^2 （RVI） is 0.664; the value of R^2 （NDVI） is 0.649 and the value of R^2 （PVI） is 0.466. （3） The value of correlation coefficient is low between the biomass and the vegetation indexes （RVI and NDVI） and the value of linear regression equation’s R^2 is 0.342 and 0.316, and the Logarithmic regression equation’s R^2 is 0.319 and 0.21, and the quadratic equation’s R^2 is 0.589 and 0.568, the value of correlation coefficient is high between the biomass and the vegetation indexes （PVI, SAVI and MSAVI）, the value of linear regression equation is 0.626, 0.698 and 0.679, that of logarithmic regression equation is 0.592, 0.706 and 0.683 and that of the quadratic equation is 0.688, 0.711 and 0.683.