Estimation of gross primary production of irrigated maize using Landsat-8 imagery and Eddy Covariance data

A study was conducted to understand the potential of Landsat-8 in the estimation of gross primary production (GPP) and to quantify the productivity of maize crop cultivated under hyper-arid conditions of Saudi Arabia. The GPP of maize crop was estimated by using the Vegetation Photosynthesis Model (VPM) utilizing remote sensing data from Landsat-8 reflectance (GPP_VPM) as well as the meteorological data provided by Eddy Covariance (EC) system (GPP_EC), for the period from August to November 2015. Results revealed that the cumulative GPP_EC for the entire growth period of maize crop was 1871 g C m^?2. However, the cumulative GPP determined as a function of the enhanced vegetation index – EVI (GPP_EVI) was 1979 g C m^?2, and that determined as a function of the normalized difference vegetation index – NDVI (GPP_NDVI) was 1754 g C m^?2. These results indicated that the GPP_EVI was significantly higher than the GPP_EC (R² = 0.96, P = 0.0241 and RMSE = 12.6%). While, the GPP_NDVI was significantly lower than the GPP_EC (R² = 0.93, P = 0.0384 and RMSE = 19.7%). However, the recorded relative error between the GPP_EC and both the GPP_EVI and the GPP_NDVI was ?6.22% and 5.76%, respectively. These results demonstrated the potential of the landsat-8 driven VPM model for the estimation of GPP, which is relevant to the productivity and carbon fluxes.