Comparison of different hyperspectral vegetation indices for canopy leaf nitrogen concentration estimation in rice

BACKGROUND AND AIMS: Variations in the water and soil background in the signal path can cause variations in canopy spectral reflectance, which leads to uncertainty in estimating the canopy nitrogen (N) status. The primary objective of this study was to explore the optimum vegetation indices that were highly correlated with canopy leaf N concentration (LNC) but less influenced by the canopy leaf area index (LAI) and vegetation coverage (VC) in rice. METHODS: A systematic analysis of the quantitative relationships between various hyperspectral vegetation indices and LNC, VC and LAI was conducted based on 4-year rice field experiments using different rice varieties, N rates and planting densities. New spectral indices were derived to estimate LNC in rice under variable vegetation coverage. RESULTS: Although the newly developed simple green ratio indices, SR (R₅₅₃, R₅₃₇) and SR (R₅₄₅, R₅₃₈), and the three-band index (R₆₀₅-R₅₂₁-R₆₈₂)/(R₆₀₅+R₅₂₁+R₆₈₂) correlated well with the LNC. Only SR (R₅₅₃, R₅₃₇) was less influenced by VC/LAI and showed a stable performance in both the independent calibration and validation datasets. For the published indices tested in the present study, NDVIg-b and ND (R₅₀₃, R₄₈₃) showed a good predictive ability for the LNC. However, both of these indices and other published indices were found to be significantly dominated by the VC/LAI. CONCLUSION: SR (R₅₅₃, R₅₃₇) was the best index to reliably estimate the LNC in rice under various cultivation conditions, and is recommended for this use. However, other spectral indices need to be examined to determine if they influenced by factors such as VC/LAI. Such studies will improve the applicability of these indices to different types of rice cultivars and production systems.