Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V

Front Matter: Volume 11414

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V ◽

10.1117/12.2572635 ◽

2020 ◽

Keyword(s):

Matter Volume

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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?

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V ◽

10.1117/12.2558777 ◽

2020 ◽

Author(s):

Ayman Nassar ◽

Alfonso F. Torres-Rua ◽

William P. Kustas ◽

Hector Nieto ◽

Mac McKee ◽

...

Keyword(s):

Energy Balance ◽

High Resolution ◽

Surface Energy ◽

Eddy Covariance ◽

Energy Balance Model ◽

Balance Model ◽

Energy Fluxes ◽

Surface Energy Fluxes ◽

High Resolution Imagery

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Implications of soil and canopy temperature uncertainty in the estimation of surface energy fluxes using TSEB2T and high-resolution imagery in commercial vineyards

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V ◽

10.1117/12.2558715 ◽

2020 ◽

Author(s):

Ayman Nassar ◽

Alfonso F. Torres-Rua ◽

William P. Kustas ◽

Hector Nieto ◽

Mac McKee ◽

...

Keyword(s):

High Resolution ◽

Surface Energy ◽

Canopy Temperature ◽

Energy Fluxes ◽

Surface Energy Fluxes ◽

High Resolution Imagery

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An open, scalable, and flexible framework for automated aerial measurement of field experiments

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V ◽

10.1117/12.2560008 ◽

2020 ◽

Author(s):

Christophe Schnaufer ◽

Julian L. Pistorius ◽

David LeBauer

Keyword(s):

Field Experiments ◽

Flexible Framework

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Discrimination between and geolocation of cotton and palmer amaranth using spectral and geometric data

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V ◽

10.1117/12.2559083 ◽

2020 ◽

Author(s):

Brandon Simmers ◽

Eddie L. Jacobs ◽

Lan Wang ◽

Alfredo J. Ramirez

Keyword(s):

Palmer Amaranth ◽

Geometric Data

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Lettuce plant health assessment using UAV-based hyperspectral sensor and proximal sensors

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V ◽

10.1117/12.2557686 ◽

2020 ◽

Author(s):

Subodh Bhandari ◽

Amar Raheja ◽

Mohammad R. Chaichi ◽

Frank H. Pham ◽

Tristan M. Sherman ◽

...

Keyword(s):

Health Assessment ◽

Plant Health ◽

Lettuce Plant ◽

Hyperspectral Sensor

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Weed identification and removal using machine learning techniques and unmanned ground vehicles

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V ◽

10.1117/12.2557625 ◽

2020 ◽

Author(s):

Mercado Espinoza ◽

Colby Z. Le ◽

Amar Raheja ◽

Subodh Bhandari

Keyword(s):

Machine Learning ◽

Machine Learning Techniques ◽

Unmanned Ground Vehicles ◽

Ground Vehicles ◽

Learning Techniques

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Estimation of evapotranspiration and energy fluxes using a deep-learning-based high-resolution emissivity model and the two-source energy balance model with sUAS information

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V ◽

10.1117/12.2558824 ◽

2020 ◽

Author(s):

Alfonso F. Torres-Rua ◽

Andres M. Ticlavilca ◽

Mahyar Aboutalebi ◽

Hector Nieto ◽

Maria M. Alsina ◽

...

Keyword(s):

Deep Learning ◽

Energy Balance ◽

High Resolution ◽

Energy Balance Model ◽

Balance Model ◽

Energy Fluxes ◽

Emissivity Model

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Investigating the potential of satellite imagery for high-throughput field phenotyping applications

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V ◽

10.1117/12.2558729 ◽

2020 ◽

Cited By ~ 1

Author(s):

Sindhuja Sankaran ◽

Chongyuan Zhang ◽

Preston Hurst ◽

Afef Marzougui ◽

Arun Narenthiran Veeranampalayam Sivakumar ◽

...

Keyword(s):

Satellite Imagery ◽

High Throughput ◽

Field Phenotyping

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The future of cooperative air and ground phenotyping

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V ◽

10.1117/12.2564696 ◽

2020 ◽

Author(s):

Alex Thomasson ◽

Xiongzhe Han

Keyword(s):

The Future

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Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V
Latest Publications

TOTAL DOCUMENTS

H-INDEX

Published By SPIE

Front Matter: Volume 11414

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?

Implications of soil and canopy temperature uncertainty in the estimation of surface energy fluxes using TSEB2T and high-resolution imagery in commercial vineyards

An open, scalable, and flexible framework for automated aerial measurement of field experiments

Discrimination between and geolocation of cotton and palmer amaranth using spectral and geometric data

Lettuce plant health assessment using UAV-based hyperspectral sensor and proximal sensors

Weed identification and removal using machine learning techniques and unmanned ground vehicles

Estimation of evapotranspiration and energy fluxes using a deep-learning-based high-resolution emissivity model and the two-source energy balance model with sUAS information

Investigating the potential of satellite imagery for high-throughput field phenotyping applications

The future of cooperative air and ground phenotyping

Export Citation Format

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By SPIE

Front Matter: Volume 11414

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?

Implications of soil and canopy temperature uncertainty in the estimation of surface energy fluxes using TSEB2T and high-resolution imagery in commercial vineyards

An open, scalable, and flexible framework for automated aerial measurement of field experiments

Discrimination between and geolocation of cotton and palmer amaranth using spectral and geometric data

Lettuce plant health assessment using UAV-based hyperspectral sensor and proximal sensors

Weed identification and removal using machine learning techniques and unmanned ground vehicles

Estimation of evapotranspiration and energy fluxes using a deep-learning-based high-resolution emissivity model and the two-source energy balance model with sUAS information

Investigating the potential of satellite imagery for high-throughput field phenotyping applications

The future of cooperative air and ground phenotyping

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V
Latest Publications