Data

SMART Farms Pasture Sampling Data

University of New England, Australia
Schneider, Derek
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25952/jqy8-3a89&rft.title=SMART Farms Pasture Sampling Data&rft.identifier=10.25952/jqy8-3a89&rft.publisher=University of New England&rft.description=This data set contains the results from pasture sampling campaigns performed on the UNE SMART Farms. Monthly sampling began in December 2018 and is ongoing, as of February 2021. Sampling is designed to generate data suitable for building and validating pasture monitoring models and algorithms utilising optical remote sensing and proximally sensed pasture monitoring platforms. On each sampling date up to 10 locations are chosen and 3 replicate samples are taken at each site. Sites are chosen that are relatively uniform in nature. Replicates are chosen which act to describe the general area, we perform a cut at a location that visual appears average for the surrounding ~100m2, slightly above average and slightly below average. This allows for correlation with satellite data of multiple spatial resolution. The data set includes objective NDVI data taken with a Holland Scientific ACS211 CropCircle, pasture height information and an estimate of green percentage, along with subjective visual estimates of pasture parameters which correspond to each physical pasture cut. Access and further information about the dataset can be obtained by contacting the dataset creator.Please contact Derek Schneider (dschnei5@une.edu.au) for access to the dataset.&rft.creator=Schneider, Derek &rft.date=2021&rft.coverage=151.59032730102535,-30.43422092679961 151.58979321899469,-30.467356827806153 151.6979398045628,-30.467691079535552 151.69700525689407,-30.39652843057612 151.5907945748536,-30.39587441263716&rft_rights= http://creativecommons.org/licenses/by-nc-nd/4.0/&rft_rights=&rft_rights=Rights holder: Derek Schneider&rft_subject=Farming Systems Research&rft_subject=AGRICULTURAL AND VETERINARY SCIENCES&rft_subject=AGRICULTURE, LAND AND FARM MANAGEMENT&rft_subject=Pasture, Browse and Fodder Crops not elsewhere classified&rft_subject=ANIMAL PRODUCTION AND ANIMAL PRIMARY PRODUCTS&rft_subject=PASTURE, BROWSE AND FODDER CROPS&rft_subject=Native and Residual Pastures&rft_subject=Sown Pastures (excl. Lucerne)&rft_subject=Agricultural systems analysis and modelling&rft_subject=Agriculture, land and farm management&rft_subject=AGRICULTURAL, VETERINARY AND FOOD SCIENCES&rft_subject=100503 Native and residual pastures&rft_subject=100505 Sown pastures (excl. lucerne)&rft.type=dataset&rft.language=English Access the data

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Contact Information

dschnei5@une.edu.au

Full description

This data set contains the results from pasture sampling campaigns performed on the UNE SMART Farms. Monthly sampling began in December 2018 and is ongoing, as of February 2021. Sampling is designed to generate data suitable for building and validating pasture monitoring models and algorithms utilising optical remote sensing and proximally sensed pasture monitoring platforms. On each sampling date up to 10 locations are chosen and 3 replicate samples are taken at each site. Sites are chosen that are relatively uniform in nature. Replicates are chosen which act to describe the general area, we perform a cut at a location that visual appears average for the surrounding ~100m2, slightly above average and slightly below average. This allows for correlation with satellite data of multiple spatial resolution. The data set includes objective NDVI data taken with a Holland Scientific ACS211 CropCircle, pasture height information and an estimate of green percentage, along with subjective visual estimates of pasture parameters which correspond to each physical pasture cut. Access and further information about the dataset can be obtained by contacting the dataset creator.
Please contact Derek Schneider (dschnei5@une.edu.au) for access to the dataset.

Issued: 2021-02-25

This dataset is part of a larger collection

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151.59033,-30.43422 151.58979,-30.46736 151.69794,-30.46769 151.69701,-30.39653 151.59079,-30.39587

151.64386651178,-30.431782746086

Identifiers