title: Optimal waveband identification for estimation of leaf area index of paddy rice.
abstract: The objectives of the study were to select suitable wavebands for rice leaf area index (LAI) estimation using the data acquired over a whole growing season, and to test the efficiency of the selected wavebands by comparing them with feature positions of rice canopy spectra. In this study, the field experiment in 2002 growing season was conducted at the experimental farm of Zhejiang University, Hangzhou, China. Measurements of hyperspectral reflectance (350 approximately 2500 nm) and corresponding LAI were made for a paddy rice canopy throughout the growing season. And three methods were employed to identify the optimal wavebands for paddy rice LAI estimation: correlation coefficient-based method, vegetation index-based method, and stepwise regression method. This research selected 15 wavebands in the region of 350~2 500 nm, which appeared to be the optimal wavebands for the paddy rice LAI estimation. Of the selected wavebands, the most frequently occurring wavebands were centered around 554, 675, 723, and 1 633 nm. They were followed by 444, 524, 576, 594, 804, 849, 974, 1 074, 1 219, 1 510, and 2 194 nm. Most of them made physical sense and had their counterparts in spectral known feature positions, which indicates the promising potential of the 15 selected wavebands for the retrieval of paddy rice LAI.
authors.affiliation: Institute of Agricultural Remote Sensing and Information Application, Zhejiang University, Hangzhou 310029, China.
authors.forename: Fu-min
authors.initials: FM
authors.lastname: Wang
authors.forename: Jing-feng
authors.initials: JF
authors.lastname: Huang
authors.forename: Qi-fa
authors.initials: QF
authors.lastname: Zhou
authors.forename: Xiu-zhen
authors.initials: XZ
authors.lastname: Wang
mesh_terms: D012275:Oryza / Q000033:anatomy & histology / Q000254:growth & development*; D018515:Plant Leaves / Q000033:anatomy & histology