Rice and wheat are mainly planted in a row structure in China. Radiative transfer models have the potential to provide an accurate description of the bidirectional reflectance characteristics of the canopies of row-planted crops, but few of them have addressed the problem of row-planted structures. In this paper, a new 4SAIL-RowCrop model for row-planted rice and wheat canopies was developed by integrating the 4SAIL model and the Kimes geometric model. The Kimes model and the Kimes-Porous geometric optics (GO) module were used to simulate different scene component proportions. Spectral reflectance and transmittance were subsequently calculated using the 4SAIL model to determine the reflectance of crucial scene components: the illuminated canopy, illuminated background and shadowed background. The model was validated by measuring the reflectance of rice and wheat cultivars at different growth stages, planting densities and nitrogen fertilization rates. The directional and nadir reflectance simulated by the model agreed well with experimental data, with squared correlation coefficients of 0.69 and 0.98, root mean square errors of 0.013 and 0.009 and normalized root mean square errors of 15.8% and 12.4%, respectively. The results indicate that the 4SAIL-RowCrop model is suitable for simulating the spectral reflectance of the canopy of row-planted rice and wheat.
Variations in water and soil backgrounds can a ect canopy spectral re ectance, complicating canopy N status estimation. We created rice (Oryza sativa L.) canopies with varying levels of leaf area index (LAI) and water and soil backgrounds using di erent rice varieties and a combination of di erent N rates and planting densities. e quantitative relationships between hyperspectral vegetation indices and leaf nitrogen accumulation (LNA) were analyzed to derive new spectral indices and models for estimating LNA. e sensitive spectral region of LNA signi cantly di ered from that of leaf nitrogen concentration (LNC). All two-band hyperspectral vegetation indices derived from the systematic combinations of bands in the 400 to 2500 nm range were correlated to canopy LNA. e new, simple vegetation index SR(R 770 , R 752 ) exhibited the highest correlation with LNA, with R 2 0.88 for model calibration and with R 2 0.80 for model validation, respectively. e SR(R 770 , R 752 ) was modi ed by incorporating a coe cient of soil/water line parameter, q, yielding the simple vegetation index SR 2 (R 770 , R 752 ). Th is modifi ed index provided slightly better estimates of rice LNA, with a calibration R 2 0.90 and a validation R 2 0.80. Datasets obtained for di erent sensor heights before and a er canopy closure con rmed the superior performance of SR 2 (R 770 , R 752 ). erefore, the SR(R 770 , R 752 ) and SR 2 (R 770 , R 752 ) can be used to estimate rice LNA. Since SR 2 (R 770 , R 752 ) is less dominated by soil background, this index is recommended for estimating LNA in rice under various cultivation conditions.
Canopy structural parameters and light radiation are important for evaluating the light use efficiency and grain yield of crops. Their spatial variation within canopies and temporal variation over growth stages could be simulated using dynamic models with strong application and predictability. Based on an optimized canopy structure vertical distribution model and the Beer-Lambert law combined with hyperspectral remote sensing (RS) technology, we established a new dynamic model for simulating leaf area index (LAI), leaf angle (LA) distribution and light radiation at different vertical heights and growth stages. The model was validated by measuring LAI, LA and light radiation in different leaf layers at different growth stages of two different types of rice (Oryza sativa L.), i.e., japonica (Wuxiangjing14) and indica (Shanyou63). The results show that the simulated values were in good agreement with the observed values, with an average RRMSE (relative root mean squared error) between simulated and observed LAI and LA values of 14.75% and 21.78%, respectively. The RRMSE values for simulated photosynthetic active radiation (PAR) transmittance and interception rates were 14.25% and 9.22% for Wuxiangjing14 and 15.71% and 4.40% for Shanyou63, respectively. In addition, the corresponding RRMSE values for red (R), green (G)
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