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Use of Aggieair UAS Remote Sensing Data to Estimate Crop ET at High Spatial Resolution
Synergy in Science: Partnering for Solutions 2015 Annual Meeting
  • Manal Elarab, Utah State University
  • Alfonso F. Torres-Rua, Utah State University
  • William Kustas, USDA-ARS Hydrology and Remote Sensing Lab
  • Hector Nieto, University of Copenhagen
  • Lisheng Song, Beijing Normal University
  • Joseph G. Alfieri, USDA-ARS
  • John H. Prueger, National Laboratory for Agriculture and the Environment
  • Lynn McKee, USDA-ARS
  • Martha Anderson, USDA-ARS Hydrology and Remote Sensing Laboratory
  • Luis Sanchez, E&J Gallo, Inc
  • Mima Alsina, E&J Gallo, Inc
  • Larry Hipps, Utah State University
  • Austin Jensen, Utah State University
  • Mac McKee, Utah State University
Document Type
Conference Paper
Publisher
Entomological Society of America
Location
Minneapolis, MN
Publication Date
11-17-2015
Abstract

Estimation of the spatial distribution of evapotranspiration (ET) based on remotely sensed imagery has become useful for managing water in irrigated agricultural at various spatial scales. However, data acquired by conventional satellites (Landsat, ASTER, etc.) lack the spatial resolution to capture variability of interest to support many types of precision farming applications. In this study, an unmanned aerial system (UAS), or “drone”, called AggieAirTM, was used to acquire high-resolution imagery in the visual, near infrared and thermal infrared spectra (0.15m resolution for visual and near infrared and 0.6m resolution for thermal infrared) over a vineyard study site being monitored as part of the Grape Remote sensing Atmospheric Profiling and Evapotranspiration eXperiment (GRAPEX)near Lodi, California. The imagery was used as input to (1) a surface energy balance model based on the Mapping Evapotranspiration with Internalized Calibration (METRIC) modeling approach, which was originally developed to use Landsat data and (2) the Two-Source Energy Balance (TSEB) model to produce ET maps at high spatial resolutions. Data from flux towers located at the site were used to evaluate the performance of these two models applied to the high resolution remote sensing data in estimating ET. A comparison of the spatial distribution in METRIC and TSEB model output over the vineyards will be discussed and will highlight the similarities and differences in ET estimation from the two methodologies and the utility of the two approaches using high resolution imagery for mapping ET in vineyards.

Citation Information
Manal Elarab, Alfonso F. Torres-Rua, William Kustas, Hector Nieto, et al.. "Use of Aggieair UAS Remote Sensing Data to Estimate Crop ET at High Spatial Resolution" Synergy in Science: Partnering for Solutions 2015 Annual Meeting (2015)
Available at: http://works.bepress.com/alfonso-torres/123/