Carbon Use Efficiency of the First Ratoon Cane by Eddy Covariance Technique

Pakoktom, Tiwa; Chaichana, Nongpat; Phattaralerphong, Jessada; Sathornkich, Jate

doi:10.7763/ijesd.2013.v4.400

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…The resultant GPP (hereafter GPP EC ) is utilized as the standard data to evaluate vegetation phenology, as well as GPP estimates derived from process-based models and data-driven models over multiple spatial and temporal resolutions [27][28][29] (p. 200). However, because of the high cost and complexity associated with the operation of EC sites, to date, the carbon and water fluxes of sugarcane plantations have only been measured at a few sites worldwide [30][31][32][33][34][35]. Time-series data of the carbon and water fluxes from these sites provide information on sugarcane crop phenology, GPP, and evapotranspiration.…”

Section: Introductionmentioning

confidence: 99%

Improved Modeling of Gross Primary Production and Transpiration of Sugarcane Plantations with Time-Series Landsat and Sentinel-2 Images

Celis,

Xiao,

White

et al. 2023

Remote Sensing

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Sugarcane croplands account for ~70% of global sugar production and ~60% of global ethanol production. Monitoring and predicting gross primary production (GPP) and transpiration (T) in these fields is crucial to improve crop yield estimation and management. While moderate-spatial-resolution (MSR, hundreds of meters) satellite images have been employed in several models to estimate GPP and T, the potential of high-spatial-resolution (HSR, tens of meters) imagery has been considered in only a few publications, and it is underexplored in sugarcane fields. Our study evaluated the efficacy of MSR and HSR satellite images in predicting daily GPP and T for sugarcane plantations at two sites equipped with eddy flux towers: Louisiana, USA (subtropical climate) and Sao Paulo, Brazil (tropical climate). We employed the Vegetation Photosynthesis Model (VPM) and Vegetation Transpiration Model (VTM) with C4 photosynthesis pathway, integrating vegetation index data derived from satellite images and on-ground weather data, to calculate daily GPP and T. The seasonal dynamics of vegetation indices from both MSR images (MODIS sensor, 500 m) and HSR images (Landsat, 30 m; Sentinel-2, 10 m) tracked well with the GPP seasonality from the EC flux towers. The enhanced vegetation index (EVI) from the HSR images had a stronger correlation with the tower-based GPP. Our findings underscored the potential of HSR imagery for estimating GPP and T in smaller sugarcane plantations.

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Section: Introductionmentioning

confidence: 99%

Improved Modeling of Gross Primary Production and Transpiration of Sugarcane Plantations with Time-Series Landsat and Sentinel-2 Images

Celis,

Xiao,

White

et al. 2023

Remote Sensing

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“…The measured NEE EC data and estimated ER EC and GPP EC data have been used as standard or reference data for the assessment of vegetation phenology and biogeochemical models that estimate these CO 2 fluxes across site, regional, and global scales [14,15]. To date, only a small number of EC tower sites have been operated to measure the CO 2 fluxes of sugarcane plantations [16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

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

Xin

Xiao

Cabral³

et al. 2020

Remote Sensing

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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.

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“…The disadvantage of the CC method is the disturbance of the measurement point and the limitation of site and time periods, which theoretically requires more than 100 replications for a representative measurement of one site [12]. The EC method can measure continuously without disturbing the environment and can cover a few hectares, up to a large scale [13,14]. The disadvantage of the EC method is that this method requires a flat and homogeneous managed area according to canopy height and wind speed [15].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Closed Chamber and Eddy Covariance Methods to Improve the Understanding of Methane Fluxes from Rice Paddy Fields in Japan

et al. 2018

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Greenhouse gas flux monitoring in ecosystems is mostly conducted by closed chamber and eddy covariance techniques. To determine the relevance of the two methods in rice paddy fields at different growing stages, closed chamber (CC) and eddy covariance (EC) methods were used to measure the methane (CH4) fluxes in a flooded rice paddy field. Intensive monitoring using the CC method was conducted at 30, 60 and 90 days after transplanting (DAT) and after harvest (AHV). An EC tower was installed at the centre of the experimental site to provide continuous measurements during the rice cropping season. The CC method resulted in CH4 flux averages that were 58%, 81%, 94% and 57% higher than those measured by the EC method at 30, 60 and 90 DAT and after harvest (AHV), respectively. A footprint analysis showed that the area covered by the EC method in this study included non-homogeneous land use types. The different strengths and weaknesses of the CC and EC methods can complement each other, and the use of both methods together leads to a better understanding of CH4 emissions from paddy fields.

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Carbon Use Efficiency of the First Ratoon Cane by Eddy Covariance Technique

Abstract: Index Terms-Carbon use efficiency, eddy covariance technique, first ratoon cane.

Cited by 3 publications

References 11 publications

Improved Modeling of Gross Primary Production and Transpiration of Sugarcane Plantations with Time-Series Landsat and Sentinel-2 Images

Improved Modeling of Gross Primary Production and Transpiration of Sugarcane Plantations with Time-Series Landsat and Sentinel-2 Images

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

Comparison of Closed Chamber and Eddy Covariance Methods to Improve the Understanding of Methane Fluxes from Rice Paddy Fields in Japan

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