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University of Idaho

Since 1889, the University of Idaho has provided motivated students with a transformative higher education experience that prepares them to solve real-world problems and achieve success in their lives and careers.

Learn more at https://www.uidaho.edu

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ANN-ET Project: 2018 Crop evapotranspiration and Neural network method

Data and Matlab scripts published in support of manuscript published in MDPI Agronomy "Using Neural Networks to Estimate Site-Specific Crop Evapotranspiration from Low Cost Sensors". This dataset includes eddy-covariance and meteorological field measurements taken in 2018 over drip irrigated hazelnut (C. avellana var.) orchards. Meta-data describing the field experiments is included in an Excel spreadsheet.

Further documentation of the neural network method can be found in the article mentioned above.

FieldValue
Modified
2019-03-18
Release Date
2019-02-13
Publisher
Identifier
b44497db-61a5-4f7d-820c-123be780e6db
NKN Identifier
b44497db-61a5-4f7d-820c-123be780e6db
Spatial / Geographical Coverage Area
POLYGON ((-123.7939453125 45.015301989992, -123.80218505859 45.435080998385, -123.01940917969 45.44054150285, -123.01940917969 45.014978407491))
Spatial / Geographical Coverage Location
Yamhill County, Oregon, USA
Temporal Coverage
Saturday, May 26, 2018 - 00:00 to Monday, June 25, 2018 - 00:00
Language
English (United States)
License
Author
Jason Kelley, Eric Pardyjak, Chad Higgins
Contact Name
Jason Kelley
Contact Email
Public Access Level
Public
DOI
10.7923/nnxk-8p22