title: [Simulation of vegetation indices optimizing under retrieval of vegetation biochemical parameters based on PROSPECT + SAIL model].
abstract: This study analyzed the sensitivities of three vegetation biochemical parameters [chlorophyll content (Cab), leaf water content (Cw), and leaf area index (LAI)] to the changes of canopy reflectance, with the effects of each parameter on the wavelength regions of canopy reflectance considered, and selected three vegetation indices as the optimization comparison targets of cost function. Then, the Cab, Cw, and LAI were estimated, based on the particle swarm optimization algorithm and PROSPECT + SAIL model. The results showed that retrieval efficiency with vegetation indices as the optimization comparison targets of cost function was better than that with all spectral reflectance. The correlation coefficients (R2) between the measured and estimated values of Cab, Cw, and LAI were 90.8%, 95.7%, and 99.7%, and the root mean square errors of Cab, Cw, and LAI were 4.73 microg x cm(-2), 0.001 g x cm(-2), and 0.08, respectively. It was suggested that to adopt vegetation indices as the optimization comparison targets of cost function could effectively improve the efficiency and precision of the retrieval of biochemical parameters based on PROSPECT + SAIL model.
authors.affiliation: School of Information Engineering, China University of Geosciences, Beijing 100083, China. wl_19830807@sohu.com
authors.forename: Ling
authors.initials: L
authors.lastname: Wu
authors.forename: Xiang-Nan
authors.initials: XN
authors.lastname: Liu
authors.forename: Bo-Tian
authors.initials: BT
authors.lastname: Zhou
authors.forename: Chuan-Hao
authors.initials: CH
authors.lastname: Liu
authors.forename: Lu-Feng
authors.initials: LF
authors.lastname: Li
mesh_terms: D000465:Algorithms; D002681:China; D002734:Chlorophyll / Q000032:analysis; D003198:Computer Simulation; D017753:Ecosystem; D008962:Models, Theoretical; D010788:Photosynthesis / Q000502:physiology; D063245:Plant Development; D018515:Plant Leaves / Q000737:chemistry*; D011891:Rain; D058998:Remote Sensing Technology; D014867:Water / Q000032:analysis
chemical_list: D014867:Water; D002734:Chlorophyll