CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 12114 > Article
Presentation
30 May 2022 Assessment of TSEB-PT and -2T in ET partitioning estimation over California commercial vineyards based on sUAS information
Rui Gao, Alfonso F. Torres-Rua, Lawrence Hipps, William P. Kustas, Martha Anderson, William A. White, Joseph G. Alfieri, Maria Mar Alsina, Nick Dokoozlian, Hector Nieto, Feng Gao, Lynn G. McKee, John H. Prueger, Luis Sanchez, Andrew J. Mcelrone, Nicolas Bambach-Ortiz, Calvin Coopmans, Ian Gowing
Author Affiliations +
Proceedings Volume 12114, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VII; 121140I (2022) https://doi.org/10.1117/12.2622993
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States
Abstract
Evapotranspiration (ET) is a crucial part of hydrological cycling, and its (ET) partitioning allows separate assessment of soil and plant water, energy, and carbon fluxes. ET partitioning plays an important role in agriculture since it is related to yield quality, irrigation efficiency, and plant growth. Satellite remote-sense-based methods provide an opportunity for ET partitioning at a subfield scale. However, one challenge is the resolution of the remote sensing data and relating these results to vine plants and irrigation subfield sections (valve units). With the small unmanned aerial system - sUAS such as AggieAir from Utah State University, ET and ET partition estimation via the two-source energy balance (TSEB) model at vineyards can be achieved. In this study, assessment of ET and ET partitioning, soil water evaporation and plant transpiration, using the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) information and aerial high-resolution imagery from AggieAir team will be performed. In specific, the performance of two implementations of the TSEB model: TSEB-PT (Priestley-Taylor approach) and TSEB-2T (dual temperature approach) on ET partitioning at a subfield scale will be evaluated, using ground and recently developed machine-learning-based Grapevine LAI imagery. The performance of the TSEB implementations will be documented for three major areas in California called Barelli, Sierra Loma, and Ripperdan, which encompasses major climatological regions in the state.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Rui Gao, Alfonso F. Torres-Rua, Lawrence Hipps, William P. Kustas, Martha Anderson, William A. White, Joseph G. Alfieri, Maria Mar Alsina, Nick Dokoozlian, Hector Nieto, Feng Gao, Lynn G. McKee, John H. Prueger, Luis Sanchez, Andrew J. Mcelrone, Nicolas Bambach-Ortiz, Calvin Coopmans, and Ian Gowing "Assessment of TSEB-PT and -2T in ET partitioning estimation over California commercial vineyards based on sUAS information", Proc. SPIE 12114, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VII, 121140I (30 May 2022); https://doi.org/10.1117/12.2622993
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 PRESENTATION
WATCH
PRESENTATION SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
KEYWORDS
Remote sensing
Agriculture
Atmospheric sensing
Carbon
Climatology
Performance modeling
Satellites
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top