title: [Inversion of leaf area index during different growth stages in winter wheat].
abstract: Being orientated to the low prescion of crop leaf area index (LAI) inversion using the same spectral vegetation index during different crop growth stages, the present paper analyzed the precision of LAI inversion by employing NDVI(normalized difference vegetation index). Ten vegetation indices were chosen including six broad-band vegetation indices and four narrow-band vegetation indices responding to vegetation cover to inverse LAI in different growth stages. Several conclusions were drawn according to the analysis. The determinant coefficient (R2) and root mean square error (RMSE) between LAI inversion value and true value were 0.5585 and 0.3209 respectively during the whole growth duraton. The mSR (modified simple ratio index) index was appropriate to inverse of LAI during earlier growth stages (before jointing stage) in winter wheat. The R2 and RMSE between LAI inversion value and true value were 0.7287 and 0.2971 respectively. The SR (simple ratio index) index was suitable enough to inverse of LAI during medium growth stages (from joingting stagess to heading stages). The R2 and RMSE between LAI inversion value and true value were 0.6546 and 0.3061 respectively. The NDVI (normalized difference vegetation index) index was proven to be fine to inverse LAI during later growth stages(from heading stage to ripening stage). The R2 and RMSE between LAI inversion value and true value were 0.6794 and 0.3164 respectively. Therefore it was indicated that the results of LAI inversion was much better inverse of winter wheat LAI choosing different vegetation indices during differen growth stages for winter wheat according to the change of vegetation cover and canopy reflectance than merely with NDVI to inverse LAI in the whole growth stages. It was concluded that the precision of LAI inversion was significantly improved with segmented models based on different vegetation indices.
authors.affiliation: Key Laboratory of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China. zhaojuan@ceode.ac.cn
authors.forename: Juan
authors.initials: J
authors.lastname: Zhao
authors.affiliation: Key Laboratory of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China.
authors.forename: Wen-jiang
authors.initials: WJ
authors.lastname: Huang
authors.affiliation: Key Laboratory of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China.
authors.forename: Yao-hong
authors.initials: YH
authors.lastname: Zhang
authors.affiliation: School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China.
authors.forename: Yuan-shu
authors.initials: YS
authors.lastname: Jing
mesh_terms: D008962:Models, Theoretical; D018515:Plant Leaves / Q000254:growth & development*; D013057:Spectrum Analysis; D014908:Triticum / Q000254:growth & development*