Literature DB >> 33758459

To What Extend Does the Eddy Covariance Footprint Cutoff Influence the Estimation of Surface Energy Fluxes Using Two Source Energy Balance Model and High-Resolution Imagery in Commercial Vineyards?

Ayman Nassar1, Alfonso Torres-Rua1, William Kustas2, Hector Nieto3, Mac McKee1, Lawrence Hipps4, Joseph Alfieri2, John Prueger5, Maria Mar Alsina6, Lynn McKee2, Calvin Coopmans7, Luis Sanchez6, Nick Dokoozlian6.   

Abstract

Validation of surface energy fluxes from remote sensing sources is performed using instantaneous field measurements obtained from eddy covariance (EC) instrumentation. An eddy covariance measurement is characterized by a footprint function / weighted area function that describes the mathematical relationship between the spatial distribution of surface flux sources and their corresponding magnitude. The orientation and size of each flux footprint / source area depends on the micro-meteorological conditions at the site as measured by the EC towers, including turbulence fluxes, friction velocity (ustar), and wind speed, all of which influence the dimensions and orientation of the footprint. The total statistical weight of the footprint is equal to unity. However, due to the large size of the source area / footprint, a statistical weight cutoff of less than one is considered, ranging between 0.85 and 0.95, to ensure that the footprint model is located inside the study area. This results in a degree of uncertainty when comparing the modeled fluxes from remote sensing energy models (i.e., TSEB2T) against the EC field measurements. In this research effort, the sensitivity of instantaneous and daily surface energy flux estimates to footprint weight cutoffs are evaluated using energy balance fluxes estimated with multispectral imagery acquired by AggieAir sUAS (small Unmanned Aerial Vehicle) over commercial vineyards near Lodi, California, as part of the ARS-USDA Agricultural Research Service's Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project. The instantaneous fluxes from the eddy covariance tower will be compared against instantaneous fluxes obtained from different TSEB2T aggregated footprint weights (cutoffs). The results indicate that the size, shape, and weight of pixels inside the footprint source area are strongly influenced by the cutoff values. Small cutoff values, such as 0.3 and 0.35, yielded high weights for pixels located within the footprint domain, while large cutoffs, such as 0.9 and 0.95, result in low weights. The results also indicate that the distribution of modelled LE values within the footprint source area are influenced by the cutoff values. A wide variation in LE was observed at high cutoffs, such as 0.90 and 0.95, while a low variation was observed at small cutoff values, such as 0.3. This happens due to the large number of pixel units involved inside the footprint domain when using high cutoff values, whereas a limited number of pixels are obtained at lower cutoff values.

Entities:  

Keywords:  Kljun EC footprint model; TSEB2T model; eddy covariance (EC); energy fluxes; footprint / source area; footprint cutoff; latent heat flux (LE); spatial analysis

Year:  2020        PMID: 33758459      PMCID: PMC7982303          DOI: 10.1117/12.2558777

Source DB:  PubMed          Journal:  Proc SPIE Int Soc Opt Eng        ISSN: 0277-786X


  4 in total

1.  Estimation of surface thermal emissivity in a vineyard for UAV microbolometer thermal cameras using NASA HyTES hyperspectral thermal, Landsat and AggieAir optical data.

Authors:  Alfonso Torres-Rua; Mahyar Aboutalebi; Timothy Wright; Ayman Nassar; Pierre Guillevic; Lawrence Hipps; Feng Gao; Kevin Jim; Maria Mar Alsina; Calvin Coopmans; Mac McKee; William Kustas
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2019-05-14

2.  Implications of sensor inconsistencies and remote sensing error in the use of small unmanned aerial systems for generation of information products for agricultural management.

Authors:  Mac McKee; Ayman Nassar; Alfonso Torres-Rua; Mahyar Aboutalebi; William Kustas
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2018-05-21

3.  Influence of Model Grid Size on the Estimation of Surface Fluxes Using the Two Source Energy Balance Model and sUAS Imagery in Vineyards.

Authors:  Ayman Nassar; Alfonso Torres-Rua; William Kustas; Hector Nieto; Mac McKee; Lawrence Hipps; David Stevens; Joseph Alfieri; John Prueger; Maria Mar Alsina; Lynn McKee; Calvin Coopmans; Luis Sanchez; Nick Dokoozlian
Journal:  Remote Sens (Basel)       Date:  2020       Impact factor: 4.848

4.  Vicarious Calibration of sUAS Microbolometer Temperature Imagery for Estimation of Radiometric Land Surface Temperature.

Authors:  Alfonso Torres-Rua
Journal:  Sensors (Basel)       Date:  2017-06-26       Impact factor: 3.576

  4 in total
  1 in total

1.  Evapotranspiration partitioning assessment using a machine-learning-based leaf area index and the two-source energy balance model with sUAV information.

Authors:  Rui Gao; Alfonso Torres-Rua; Ayman Nassar; Joseph Alfieri; Mahyar Aboutalebi; Lawrence Hipps; Nicolas Bambach Ortiz; Andrew J Mcelrone; Calvin Coopmans; William Kustas; William White; Lynn McKee; Maria Del Mar Alsina; Nick Dokoozlian; Luis Sanchez; John H Prueger; Hector Nieto; Nurit Agam
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2021-04-12
  1 in total

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