Estimation of the net primary productivity of winter wheat based on the near-infrared radiance of vegetation

Quantifying net primary productivity (NPP) is important for understanding the global carbon cycle and for assessing ecosystem carbon dynamics. However, uncertainties remain in NPP estimation. Using winter wheat data obtained from an experimental station in 2019, this study evaluated the ability of the near-infrared radiance of vegetation (NIRV,Rad) to estimate NPP at different time scales and established an estimation model based on NIRV,Rad, where NIRV,Rad was defined as the product of the normalized difference vegetation index (NDVI) and the near-infrared radiance. The results showed that the linear relationship between NIRV,Rad and NPP was superior to the relationship between NPP and NDVI, enhanced vegetation index-2 (EVI2), and near-infrared reflectance of vegetation (NIRV,Ref) at each time scale (hourly, daily, and growth period). The advantage of NIRV,Rad was more evident on the hourly scale, in which the R-2 of NIRV,Rad and NPP reached 0.77, whereas the R-2 values of the correlation of NDVI, EVI2, and NIRV,Refwith NPP were 0.30, 0.16, and 0.14, respectively. There existed a strong linear relationship between absorbed photosynthetically active radiation, net photosynthetic rate, leaf area index, and NIRV,Rad, which explained the good relationship between NIRV,Rad and NPP. Through a comparative analysis of the various models, the NIRV,Rad model was found to have the strongest ability to estimate NPP and the R-2, with the measured NPP reaching 0.81. The accuracy of NIRV,Rad provides a new method for estimating NPP and a scientific basis for estimating NPP using high resolution satellite remote sensing data on a regional scale.