Machine learning to extract maximum value from soil and crop variability, Raw datasets
Version 2 2024-02-20, 05:09
Version 1 2022-02-28, 00:51
dataset
posted on 2024-02-20, 05:09 authored by Rakesh DavidRakesh David, Rhiannon SchillingRhiannon Schilling, Glenn McDonaldGlenn McDonald<p dir="ltr">Pre-processed ML input data for 4 Roseworthy paddocks, B4, B3, E2, E5. Paddock names are included in the file names.</p><p dir="ltr"><br>Data includes boundary information, EM38, elevation, yield associated moisture percentage. UA and External funding agency data collection. Please contact Rhiannon Schilling (PIRSA-SARDI) Rhiannon.Schilling@sa.gov.au or Genn McDonald <a href="mailto:glenn.mcdonald@adelaide.edu.au" target="_blank">glenn.mcdonald@adelaide.edu.au</a> to request access to data.</p>
Funding
GRDC: UOA2002-007RTX
History
Related Materials
- 1.
GRDC contract code
GRDC: UOA2002-007RTXGRDC project title
Machine learning to extract maximum value from soil and crop variabilityContact email address
library@adelaide.edu.auStart date for this data collection
2007-01-01End date for this data collection
2011-12-31Spatial coverage
Roseworthy, South AustraliaAccess rights type
- Embargoed
