Data

University of Adelaide Roseworthy reference paddocks for GRDC Machine Learning project - raw and pre-processed datasets

The University of Adelaide
Schilling, Rhiannon ; David, Rakesh ; Roy, Stuart
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25909/621c285265462&rft.title=University of Adelaide Roseworthy reference paddocks for GRDC Machine Learning project - raw and pre-processed datasets&rft.identifier=https://doi.org/10.25909/621c285265462&rft.publisher=University of Adelaide&rft.description=The collection includes 4 paddocks with data including paddock boundaries, crop yield, EM38 geophysics, elevation, yield associated moisture percentage. The data accessible from the paddocks and has been acquired between 2005 and 2020. In addition to the raw data is included pre-processed data for machine learning analytics. Pre-processed data was converted to standard csv machine-readable format with CRS included for all measurements. Includes processed paddock measurements, pre-processed Remote Sensing time-series data (Landsat, resampled to 5-m resolution using bilinear interpolation) and pre-processed climate time-series data (SILO database). Readme metadata documents of processed files to assist for ML purposes. Measurements re-scaled and spatially aligned using ordinary block kriging method using locally estimated variograms. The value at each grid point represents an average interpolated value within a 5-m block, centred at the grid point.A dataset of 4 paddocks at the Roseworthy Campus, University of Adelaide, South Australia. Data includes paddock boundaries, point data EM38, elevation and yield (canola, Beans - Broad/Faba, Barley - Winter, Oats - Spring, Wheat - Durum) and moisture percentage (yield associated data). The dataset collection is from 2007 - 2011. In addition to the raw data the collection includes pre-processed versions of the dataset compliant with machine learning analytics.&rft.creator=Schilling, Rhiannon &rft.creator=David, Rakesh &rft.creator=Roy, Stuart &rft.date=2021&rft.coverage=Roseworthy Campus, University of Adelaide, South Australia&rft_rights=&rft_subject=Crop yield&rft_subject=EM38&rft_subject=Machine Learning&rft_subject=Roseworthy&rft_subject=University of Adelaide&rft_subject=canola&rft_subject=beans - broad/faba&rft_subject=barley&rft_subject=oats&rft_subject=wheat&rft_subject=Durum&rft_subject=paddock&rft_subject=AGRICULTURE, LAND AND FARM MANAGEMENT&rft_subject=AGRICULTURAL AND VETERINARY SCIENCES&rft_subject=CROP AND PASTURE PRODUCTION&rft_subject=SOIL SCIENCES&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=Climate&rft_subject=SILO database&rft_subject=Landsat&rft.type=dataset&rft.language=English Access the data

Please use the contact information below to request access to this data.

Contact Information

glenn.mcdonald@adelaide.edu.au Glenn McDonald

Licence & Rights:

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Access:

Restrictions apply

Brief description

A dataset of 4 paddocks at the Roseworthy Campus, University of Adelaide, South Australia. Data includes paddock boundaries, point data EM38, elevation and yield (canola, Beans - Broad/Faba, Barley - Winter, Oats - Spring, Wheat - Durum) and moisture percentage (yield associated data). The dataset collection is from 2007 - 2011. In addition to the raw data the collection includes pre-processed versions of the dataset compliant with machine learning analytics.

Full description

The collection includes 4 paddocks with data including paddock boundaries, crop yield, EM38 geophysics, elevation, yield associated moisture percentage. The data accessible from the paddocks and has been acquired between 2005 and 2020. In addition to the raw data is included pre-processed data for machine learning analytics. Pre-processed data was converted to standard csv machine-readable format with CRS included for all measurements. Includes processed paddock measurements, pre-processed Remote Sensing time-series data (Landsat, resampled to 5-m resolution using bilinear interpolation) and pre-processed climate time-series data (SILO database). Readme metadata documents of processed files to assist for ML purposes. Measurements re-scaled and spatially aligned using ordinary block kriging method using locally estimated variograms. The value at each grid point represents an average interpolated value within a 5-m block, centred at the grid point.

Notes

The data has been collated and pre-processed for application in the machine learning project 'Machine learning to extract maximum value from soil and crop variability - UOA2002-007RTX.'

Formats (raw): Paddocks: shapefile;  Yield data: csv;  EM38: shapefile, Elevation: csv; yield associated moisture percentage: csv

Formats (pre-processed): csv

Additional Information: Moisture % included as part of yield data. Elevation included as part of yield. Pre-processed data: Yield files cleaned to remove outliers using resource: "Electromagnetic induction sensing of soil identifies constraints to the crop yields of north-eastern Australia. Soil Research 49(7) 559-571, 2011".   Readme documentation for ML pre-processed input available with data files. Data dictionary, standards, vocabulary terms, to be discussed with UA in collaboration with AxisTech

Delivery method

Access to this collection data is restricted. The data is not publicly available. Access to the full dataset may be granted following approval of a written application. email: Glenn McDonald (glenn.mcdonald@adelaide.edu.au)

Date Submitted : 05 10 2021 to 05 10 2021

Data time period: 31 12 2006 to 29 12 2010

This dataset is part of a larger collection

Spatial Coverage And Location

text: Roseworthy Campus, University of Adelaide, South Australia