Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/11502
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dc.contributor.authorDonald, Grahamen
dc.contributor.authorAhmad, Waqaren
dc.contributor.authorHulm, Elizabethen
dc.contributor.authorTrotter, Marken
dc.contributor.authorLamb, Daviden
local.source.editorEditor(s): James Calder, Robert J Trewen
dc.date.accessioned2012-10-22T10:07:00Z-
dc.date.issued2012-
dc.identifier.citationProceedings of the First International Conference on Agro-Geoinformatics (Agro-Geoinformatics 2012), p. 157-161en
dc.identifier.isbn9781467324953en
dc.identifier.isbn9781467324946en
dc.identifier.urihttps://hdl.handle.net/1959.11/11502-
dc.description.abstractIn temperate and mediterranean regions of Australia, utilisation of pastures by grazing animals can often be as low as thirty percent. Feed budgeting is a critical strategy for improving feed utilisation and there are now pasture evaluation and monitoring programs available to farmers across Australia to enable them to estimate Pasture Growth Rate (PGR) and feed availability or Feed On Offer (FOO). Unfortunately, many farmers do not have the confidence or the time available to make regular accurate field estimates across large and remote paddocks. It is also extremely difficult to measure the spatial variation of FOO and PGR. Both satellite image-based systems, such as that derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and on-ground, active sensors and spectroradiometers have limitations. The MODIS sensor, although offering a daily acquisition interval, has a spatial resolution of 6.25ha which does create an issue in describing higher resolution spatial variation in fields and is susceptible to the unwanted artefacts associated with non-forageable vegetation such as trees. On-ground (proximal) sensors such as the Crop Circle™ instrument, can be integrated with with global positioning systems (GPS) and dataloggers and operated 'on-the-go', but field-coverage require a vast number of samples that in turn require tedious analysis and particularly if done at frequent intervals. The aim of this paper is to test whether the MODIS and Crop Circle™ data can be intergrated to provide the benefit of both high spatial and temporal resolution. Such information would be useful when determining feed on offer and pasture growth rate information at weekly or strategic times from MODIS acquisitions including other biophysical and physical relevant attributes. This electronic document is a "live" template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document.en
dc.languageenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.ispartofProceedings of the First International Conference on Agro-Geoinformatics (Agro-Geoinformatics 2012)en
dc.titleIntegrating MODIS satellite imagery and proximal vegetation sensors to enable precision livestock managementen
dc.typeConference Publicationen
dc.relation.conferenceAgro-Geoinformatics 2012: 1st International Conference on Agro-Geoinformaticsen
dc.identifier.doi10.1109/Agro-Geoinformatics.2012.6311630en
dc.subject.keywordsEnvironmental Monitoringen
local.contributor.firstnameGrahamen
local.contributor.firstnameWaqaren
local.contributor.firstnameElizabethen
local.contributor.firstnameMarken
local.contributor.firstnameDaviden
local.subject.for2008050206 Environmental Monitoringen
local.subject.seo2008829899 Environmentally Sustainable Plant Production not elsewhere classifieden
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.schoolOffice of Faculty of Science, Agriculture, Business and Lawen
local.profile.emailgdonald@une.edu.auen
local.profile.emailmtrotte3@une.edu.auen
local.profile.emaildlamb@une.edu.auen
local.output.categoryE1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-20121005-132655en
local.date.conference2nd - 4th August, 2012en
local.conference.placeShanghai, Chinaen
local.publisher.placeLos Alamitos, United States of Americaen
local.format.startpage157en
local.format.endpage161en
local.identifier.scopusid84869384742en
local.peerreviewedYesen
local.contributor.lastnameDonalden
local.contributor.lastnameAhmaden
local.contributor.lastnameHulmen
local.contributor.lastnameTrotteren
local.contributor.lastnameLamben
dc.identifier.staffune-id:gdonald2en
dc.identifier.staffune-id:mtrotte3en
dc.identifier.staffune-id:dlamben
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:11701en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleIntegrating MODIS satellite imagery and proximal vegetation sensors to enable precision livestock managementen
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.conference.detailsAgro-Geoinformatics 2012: 1st International Conference on Agro-Geoinformatics, Shanghai, China, 2nd - 4th August, 2012en
local.search.authorDonald, Grahamen
local.search.authorAhmad, Waqaren
local.search.authorHulm, Elizabethen
local.search.authorTrotter, Marken
local.search.authorLamb, Daviden
local.uneassociationUnknownen
local.year.published2012en
local.subject.for2020410599 Pollution and contamination not elsewhere classifieden
local.subject.seo2020260199 Environmentally sustainable plant production not elsewhere classifieden
local.date.start2012-08-02-
local.date.end2012-08-04-
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