NARROW BAND RATIO VEGETATION INDICES AND ITS RELATIONSHIPS WITH RICE AGRONOMIC VARIABLES

摘要

The present study aims to determine spectral bands that are best suited for characterizing rice agronomic variables. The data for this study came from ground-level hyperspectral reflectance measurements of rice at different stage. Reflectance was measured in discrete narrow bands between 350 and 2500 nm. Observed rice agronomic variables included leaf area index (LAI), wet biomass (WBM including aboveground wet biomass-AGWBM, leaf wet biomass-LWBM, stem wet biomass-SWBM), and dry biomass(DBM: including aboveground dry biomass-AGDBM, leaf dry biomass-LDBM, stem dry biomass.) Firstly, narrow band ratio vegetation index (NBRVI) involving all possible two bands combinations of discrete channels were tested. The second part of the paper describes a rigorous search procedure to identify the best NBRVI predictors of rice agronomic variables. Special narrow band lambda (λ1) versus lambda (λ2) plots of R2 values illustrates the most effective wavelength combinations (λ1 and λ2) and band-widths (△λ1 and △λ2) for predicting rice agronomic variables at different development stages. The best of the NBRVI models explained 58% to 83% variability rice agronomic variables at different development stage. A strong relationship with rice agronomic variables is located in red-edge, 700 nm to 750 nm, the longer portion of red (650nm to 700nm), the shorter portion of green (500nm to 550nm), a particular portion of NIR (800nm to 850nm). They are followed by moisture-sensitive NIR(1150nm to l200nm), and two portions of SWIR (1600nm to 1650nm).