Development of high performance computing tools for estimation of high-resolution surface energy balance products using sUAS information

Ayman Nassar; Alfonso Torres-Rua; Venkatesh Merwade; Sayan Dey; Lan Zhao; I. Luk Kim; William P. Kustas; Hector Nieto; Lawrence Hipps; Rui Gao; Joseph Alfieri; John Prueger; Maria Mar Alsina; Lynn McKee; Calvin Coopmans; Luis Sanchez; Nick Dokoozlian; Nicolas Bambach Ortiz; Andrew J. Mcelrone

doi:10.1117/12.2587763

12 April 2021 Development of high performance computing tools for estimation of high-resolution surface energy balance products using sUAS information

Ayman Nassar, Alfonso Torres-Rua, Venkatesh Merwade, Sayan Dey, Lan Zhao, I. Luk Kim, William P. Kustas, Hector Nieto, Lawrence Hipps, Rui Gao, Joseph Alfieri, John Prueger, Maria Mar Alsina, Lynn McKee, Calvin Coopmans, Luis Sanchez, Nick Dokoozlian, Nicolas Bambach Ortiz, Andrew J. Mcelrone

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Proceedings Volume 11747, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VI; 117470K (2021) https://doi.org/10.1117/12.2587763
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

sUAS (small-Unmanned Aircraft System) and advanced surface energy balance models allow detailed assessment and monitoring (at plant scale) of different (agricultural, urban, and natural) environments. Significant progress has been made in the understanding and modeling of atmosphere-plant-soil interactions and numerical quantification of the internal processes at plant scale. Similarly, progress has been made in ground truth information comparison and validation models. An example of this progress is the application of sUAS information using the Two-Source Surface Energy Balance (TSEB) model in commercial vineyards by the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment - GRAPEX Project in California. With advances in frequent sUAS data collection for larger areas, sUAS information processing becomes computationally expensive on local computers. Additionally, fragmentation of different models and tools necessary to process the data and validate the results is a limiting factor. For example, in the referred GRAPEX project, commercial software (ArcGIS and MS Excel) and Python and Matlab code are needed to complete the analysis. There is a need to assess and integrate research conducted with sUAS and surface energy balance models in a sharing platform to be easily migrated to high performance computing (HPC) resources. This research, sponsored by the National Science Foundation FAIR Cyber Training Fellowships, is integrating disparate software and code under a unified language (Python). The Python code for estimating the surface energy fluxes using TSEB2T model as well as the EC footprint analysis code for ground truth information comparison were hosted in myGeoHub site https://mygeohub.org/ to be reproducible and replicable.

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Ayman Nassar, Alfonso Torres-Rua, Venkatesh Merwade, Sayan Dey, Lan Zhao, I. Luk Kim, William P. Kustas, Hector Nieto, Lawrence Hipps, Rui Gao, Joseph Alfieri, John Prueger, Maria Mar Alsina, Lynn McKee, Calvin Coopmans, Luis Sanchez, Nick Dokoozlian, Nicolas Bambach Ortiz, and Andrew J. Mcelrone "Development of high performance computing tools for estimation of high-resolution surface energy balance products using sUAS information", Proc. SPIE 11747, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VI, 117470K (12 April 2021); https://doi.org/10.1117/12.2587763

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