title: [Research on remote sensing inversion biomass method based on the Suaeda salsa's measured spectrum].
abstract: 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 R2 is 0.711. By comparison of vegetation index linear regression equations, the correlation coefficient (SAVI and LADI) R2 is 0.696; the value of R2 (LAI and MSAV) is 0.695; the value of R2 (RVI) is 0.664; the value of R2(NDVI) is 0.649 and the value of R2 (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 R2 is 0.342 and 0.316, and the Logarithmic regression equation's R2 is 0.319 and 0.21, and the quadratic equation's R2 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.
authors.affiliation: The Center of Research for Ecology and Environment, Shanghai Normal University, Shanghai 200234, China. sdwutao@sina.com
authors.forename: Tao
authors.initials: T
authors.lastname: Wu
authors.forename: Dong-Zhi
authors.initials: DZ
authors.lastname: Zhao
authors.forename: Jian-Cheng
authors.initials: JC
authors.lastname: Kang
authors.forename: An-Ning
authors.initials: AN
authors.lastname: Suo
authors.forename: Bao-Quan
authors.initials: BQ
authors.lastname: Wei
authors.forename: Yu-Juan
authors.initials: YJ
authors.lastname: Ma
mesh_terms: D018533:Biomass; D019663:Chenopodiaceae; D002681:China; D016014:Linear Models; D018515:Plant Leaves; D058998:Remote Sensing Technology; D013057:Spectrum Analysis