Modeling gross primary production of paddy rice cropland through analyses of data from CO2 eddy flux tower sites and MODIS images

Abstract

Accurate information on the gross primary production (GPP) of paddy rice cropland is critical for assessing and monitoring rice growing conditions. The eddy co-variance technique was used to measure net ecosystem exchange (NEE) of CO 2 between paddy rice croplands and the atmosphere, and the resultant NEE data then partitioned into GPP (GPP EC ) and ecosystem respiration. In this study, we first used the GPP EC data from four paddy rice flux tower sites in South Korea, Japan and the USA to evaluate the biophysical performance of three vegetation indices: Normalized Difference Vegetation Index (NDVI); Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) in terms of phenology (crop growing seasons) and GPP EC , which are derived from images taken by Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. We also ran the Vegetation Photosynthesis Model (VPM), which is driven by EVI, LSWI, photosynthetically active radiation (PAR) and air temperature, to estimate GPP over multiple years at these four sites (GPP VPM ). The 14 site-years of simulations show that the seasonal dynamics of GPP VPM successfully tracked the seasonal dynamics of GPP EC (R 2 ＞0.88 or higher). The cross-site comparison also shows that GPP VPM agreed reasonably well with the variations of GPP EC across both years and sites. The simulation results clearly demonstrate the potential of the VPM model and MODIS images for estimating GPP of paddy rice croplands in the monsoon climates of South Korea and Japan and the Mediterranean climate in California, USA. The application of VPM to regional simulations in the near future may provide crucial GPP data to support the studies of food security and cropland carbon cycle around the world.

Fingerprint of rice paddies in spatial–temporal dynamics of atmospheric methane concentration in monsoon Asia

“…Enhanced vegetation index (EVI) is related to vegetation canopy 32 ( Supplementary Fig. 13), and has been used to estimate gross primary production of paddy rice 33 . We used MODISbased EVI as a proxy for rice plant growth to quantify the seasonal relationship between the paddy rice growth and atmospheric CH 4 concentration in a year.…”

Using digital camera and Landsat imagery with eddy covariance data to model gross primary production in restored wetlands

“…where T min , T max , and T opt are minimum, maximum, and optimal temperature for photosynthesis, respectively. As wetland plants can photosynthesize across a broad range, T min and T max were set to 0 °C and 50 °C (Larcher, 2003), and we used a value of 22 °C for T opt based on the relationship between GPP and air temperature (Xin et al, 2016). For Landsat-retrieved VIs only, W scalar was calculated using a simple approach utilizing a water-sensitive vegetation index (Oikawa et al, 2017;Xiao et al, 2004) (8) where LSWI max is the maximum land surface water index (LSWI; Table 1) within the growing season, and was estimated separately for each year (Kang et al, 2014).…”

“…Running et al, 2004;Running et al, 2000). While the MODIS GPP algorithm provides reasonable spatio-temporal patterns and variability across a diverse range of biomes and climate types (Heinsch et al, 2006), it has been shown to underestimate GPP in natural wetlands (Kang et al, 2014) and flooded rice agriculture (Xin et al, 2017), which has been attributed to the climate data, pixel heterogeneity, and the light use efficiency parameter used in the MODIS GPP model. The coarse spatial resolution (1 km) of MODIS can also be problematic for estimating wetland GPP as these ecosystems can be small in size, and highly distributed, fragmented or disconnected from other habitat types (Byrd et al, 2014).…”

Grassland Wildfires in the Southern Great Plains: Monitoring Ecological Impacts and Recovery

“…The simulation of VPM model is driven by time series images from the by MODIS and climate data (photosynthetically active radiation (PAR); air temperature). GPP data have been evaluated at many CO 2 eddy flux tower sites [24][25][26][27][28] and the results show that the VPM produces very good consistency with tower-derived GPP. The time series GPP data were acquired from at the University of Oklahoma's Earth Observation and Modeling Facility (http://www.eomf.ou.edu/ accessed on 13 December 2019).…”