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Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/28166
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DC FieldValueLanguage
dc.contributor.authorSchneider, Dereken
dc.coverage.spatial150.56 -29.53en
dc.date.accessioned2020-03-11T05:20:48Z-
dc.date.available2020-03-11T05:20:48Z-
dc.date.issued2016-03-
dc.identifier.urihttps://hdl.handle.net/1959.11/28166-
dc.description.abstractRed Normalised Difference Vegetation Index (RNDVI), Yellow Normalised Difference Vegetation Index (YNDVI), Red Simple Ratio (RSR), Yellow Simple Ratio (YSR), and apparent soil conductivity (ECa) values of a wheat (Triticum Aestivum var. Gregory) crop in the Z30 growing stage. Data was taken from Warialda, NSW using Holland Scientific Crop Circle ACS-210 Active Canopy Sensor and a Geonics EM38-MK2 operating in dipole mode.en
dc.format.extentComma Separated Values (CSV) fileen
dc.languageenen
dc.publisherUniversity of New Englanden
dc.relation.uriAccess to related Thesis provided at the following link: https://rune.une.edu.au/web/handle/1959.11/28167en
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.titleRemotely sensed data of a NSW wheat crop with 2-class fertiliser requirement labelsen
dc.typeDataseten
dcterms.accessRightsOpenen
dc.identifier.projectEmbedded Machine-Learning for Variable-Rate Fertiliser Systems: A Model-Driven Approach to Precision Agricultureen
dc.subject.keywordsOptical Remote Sensingen
dc.subject.keywordsNormalised Difference Vegetation Indexen
dc.subject.keywordsWheaten
dc.subject.keywordsFertiliser Requirementsen
dc.subject.keywordsSoil Conductivityen
dc.subject.keywordsPrecision Agricultureen
dc.subject.keywordsTriticum aestivum var. Gregoryen
local.contributor.firstnameDereken
local.subject.for2008070101 Agricultural Land Managementen
local.subject.for2008070306 Crop and Pasture Nutritionen
local.subject.for2008080309 Software Engineeringen
local.subject.seo2008960904 Farmland, Arable Cropland and Permanent Cropland Land Managementen
local.subject.seo2008961402 Farmland, Arable Cropland and Permanent Cropland Soilsen
local.subject.seo2008890299 Computer Software and Services not elsewhere classifieden
local.profile.schoolSchool of Science and Technologyen
local.profile.emaildschnei5@une.edu.auen
local.output.categoryXen
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeArmidale, Australiaen
local.access.fulltextYesen
local.contributor.lastnameSchneideren
dc.identifier.staffune-id:dschnei5en
local.profile.orcid0000-0002-1897-4175en
local.profile.rolecreatoren
local.identifier.unepublicationidune:1959.11/28166en
dc.identifier.academiclevelAcademicen
local.title.maintitleRemotely sensed data of a NSW wheat crop with 2-class fertiliser requirement labelsen
local.output.categorydescriptionX Dataseten
local.search.authorSchneider, Dereken
dcterms.rightsHolder.managedbyGregory Falzonen
local.datasetcontact.nameGregory Falzonen
local.datasetcontact.emailgfalzon2@une.edu.auen
local.datasetcustodian.nameGregory Falzonen
local.datasetcustodian.emailgfalzon2@une.edu.auen
local.datasetcontact.detailsGregory Falzon - gfalzon2@une.edu.auen
local.datasetcustodian.detailsGregory Falzon - gfalzon2@une.edu.auen
dcterms.ispartof.projectEmbedded Machine-Learning for Variable-Rate Fertiliser Systems: A Model-Driven Approach to Precision Agricultureen
dcterms.source.datasetlocationUniversity of New Englanden
local.istranslatedNoen
local.uneassociationUnknownen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2016en
local.subject.for2020300202 Agricultural land managementen
local.subject.for2020300407 Crop and pasture nutritionen
local.subject.for2020461201 Automated software engineeringen
local.subject.seo2020180607 Terrestrial erosionen
local.subject.seo2020180603 Evaluation, allocation, and impacts of land useen
local.subject.seo2020180605 Soilsen
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School of Science and Technology
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