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 (GPPVPM) as well as the meteorological data provided by Eddy Covariance (EC) system (GPPEC), for the period from August to November 2015. Results revealed that the cumulative GPPECfor 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 (GPPEVI) was 1979 g C m-2, and that determined as a function of the normalized difference vegetation index - NDVI (GPPNDVI) was 1754 g C m-2. These results indicated that the GPPEVIwas significantly higher than the GPPEC(R2= 0.96,P= 0.0241 and RMSE = 12.6%). While, the GPPNDVIwas significantly lower than the GPPEC(R2= 0.93,P= 0.0384 and RMSE = 19.7%). However, the recorded relative error between the GPPECand both the GPPEVIand the GPPNDVIwas -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.
Precision Agriculture Research Chair, King Saud University, Riyadh, Saudi Arabia.
Rangaswamy
R
Madugundu
Precision Agriculture Research Chair, King Saud University, Riyadh, Saudi Arabia; Department of Agricultural Engineering, College of Food and Agriculture Sciences, King Saud University, Riyadh, Saudi Arabia.
Khalid A
KA
Al-Gaadi
Precision Agriculture Research Chair, King Saud University, Riyadh, Saudi Arabia.
ElKamil
E
Tola
Department of Agricultural Engineering, College of Food and Agriculture Sciences, King Saud University, Riyadh, Saudi Arabia.
Ahmed G
AG
Kayad
Forestry and Ecology Group, National Remote Sensing Center, Indian Space Research Organization, Hyderabad, India.
Chandra Sekhar
CS
Jha
Carbon flux; Eddy covariance; Maize crop; Remote sensing