Understanding the Land Surface Phenology and Gross Primary Production of Sugarcane Plantations by Eddy Flux Measurements, MODIS Images, and Data-Driven Models

Fengfei Xin,Osvaldo M.R Cabral,Xiangming Xiao,Haiqiang Guo,Paul M White,Bin Zhao,Jun Ma,Bo Li

doi:10.3390/rs12142186

Abstract

Sugarcane (complex hybrids of Saccharum spp., C4 plant) croplands provide cane stalk feedstock for sugar and biofuel (ethanol) production. It is critical for us to analyze the phenology and gross primary production (GPP) of sugarcane croplands, which would help us to better understand and monitor the sugarcane growing condition and the carbon cycle. In this study, we combined the data from two sugarcane EC flux tower sites in Brazil and the USA, images from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, and data-driven models to study the phenology and GPP of sugarcane croplands. The seasonal dynamics of climate, vegetation indices from MODIS images, and GPP from two sugarcane flux tower sites (GPPEC) reveal the temporal consistency in sugarcane phenology (crop calendar: green-up dates and harvesting dates) as estimated by the vegetation indices and GPPEC data. The Land Surface Water Index (LSWI) is shown to be useful to delineate the phenology of sugarcane croplands. The relationship between the sugarcane GPPEC and the Enhanced Vegetation Index (EVI) is stronger than the relationship between the GPPEC and the Normalized Difference Vegetation Index (NDVI). We ran the Vegetation Photosynthesis Model (VPM), which uses the light use efficiency (LUE) concept and is driven by climate data and MODIS images, to estimate the daily GPP at the two sugarcane sites (GPPVPM). The seasonal dynamics of the GPPVPM and GPPEC at the two sites agreed reasonably well with each other, which indicates that VPM is a powerful tool for estimating the GPP of sugarcane croplands in Brazil and the USA. This study clearly highlights the potential of combining eddy covariance technology, satellite-based remote sensing technology, and data-driven models for better understanding and monitoring the phenology and GPP of sugarcane croplands under different climate and management practices.

Highlights

IntroductionSugarcane (complex hybrids of Saccharum spp.) is one of the major cash crops in the world [1]
Sugarcane is one of the major cash crops in the world [1]
We evaluated the effects of air temperature on the GPPEC by the relationships between the GPPEC

Summary

Introduction

Sugarcane (complex hybrids of Saccharum spp.) is one of the major cash crops in the world [1]. It accounts for 70% of the world’s sugar production [2] and is a major source of biomass feedstock for biofuel (ethanol) production [3,4]. The carbon fluxes of sugarcane plantations have large uncertainty across the spatial and temporal scales, driven by climate change [5], agricultural management practices [6,7,8,9,10], and land use change [11,12]. There is a need to observe and predict the phenology and carbon fluxes of sugarcane plantations under diverse weather and crop management practices with in situ measurement, remote sensing, and biogeochemical models across various temporal and spatial scales

Methods

Results

Conclusion