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 2017 over center pivot irrigated green bean crop (P. vulgaris). 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.
Data and Resources
Field | Value |
---|---|
Modified | 2019-03-18 |
Release Date | 2019-02-13 |
Publisher | |
Identifier | 0ebfc453-ab5e-46de-9ab6-ff1ebd0182f0 |
NKN Identifier | 0ebfc453-ab5e-46de-9ab6-ff1ebd0182f0 |
Spatial / Geographical Coverage Area | POLYGON ((-123.60717773438 44.308847344585, -123.60717773438 44.79814362449, -123.12377929688 44.79814362449, -123.12377929688 44.308847344585)) |
Spatial / Geographical Coverage Location | Benton County, Oregon, USA |
Temporal Coverage | Monday, June 12, 2017 - 00:00 to Tuesday, September 5, 2017 - 00:00 |
Language | English (United States) |
License | |
Author | |
Contact Name | Jason Kelley |
Contact Email | |
Public Access Level | Public |
DOI | 10.7923/7nt0-7e64 |