Quantifying ET and Carbon Fluxes at Crop Scale by Integrating AmeriFlux and Remote Sensing Data

Abstract:

A practical and reliable way to estimate field-scale evapotranspiration (ET) and CO2 fluxes can significantly help with optimization of water use and other sustainable practices in precision agriculture and ecosystem restoration. AmeriFlux is a “Big Data” framework updated through a tower-network that provides ecosystem measurements including water, greenhouse gas (GHG) and energy fluxes. Its sites are located in North, Central and South America, but they are limited to one or a few points in the region. The main focus of our research is to develop an effective and wide-ranging methodology for field-scale hydrological and carbon flux estimations based on the integration of AmeriFlux data and satellite images.

The AmeriFlux data we use cover a pair of commercially farmed, adjacent rice fields located in Lonoke County, Arkansas for the period 2016–2018. We first illustrate that there is significant and numerically large correlation between the ET measurements and CO2 fluxes made at the AmeriFlux sites and land surface products derived from satellite remotely sensed data (normalized difference vegetation index (NDVI), air temperature, precipitation, and surface pressure) derived by Landsat-8 and Sentinel-2 sensors. Linear regression and random forest models were then developed for predictions. We will explore the spatial and temporal pattern of the data in the future analysis, as well as integrate with local high resolution geophysical data to better understand the effect of the soil spatial heterogeneity, which is known to impact plant development.

We envision that the integration of such methodology with eco-hydrological models will enable capabilities to better estimate water use efficiency and carbon storage potential at the field-scale.