Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/23037
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dc.contributor.authorJohansen, Kasperen
dc.contributor.authorSallam, Naderen
dc.contributor.authorRobson, Andrewen
dc.contributor.authorSamson, Peteren
dc.contributor.authorChandler, Keithen
dc.contributor.authorDerby, Lisaen
dc.contributor.authorEaton, Allenen
dc.contributor.authorJennings, Jillianen
dc.date.accessioned2018-05-18T15:47:00Z-
dc.date.issued2018-
dc.identifier.citationGIScience and Remote Sensing, 55(2), p. 285-305en
dc.identifier.issn1943-7226en
dc.identifier.issn1548-1603en
dc.identifier.urihttps://hdl.handle.net/1959.11/23037-
dc.description.abstractThe greyback canegrub ('Dermolepida albohirtum') is the main pest of sugarcane crops in all cane-growing regions between Mossman (16.5°S) and Sarina (21.5°S) in Queensland, Australia. In previous years, high infestations have cost the industry up to $40 million. However, identifying damage in the field is difficult due to the often impenetrable nature of the sugarcane crop. Satellite imagery offers a feasible means of achieving this by examining the visual characteristics of stool tipping, changed leaf color, and exposure of soil in damaged areas. The objective of this study was to use geographic object-based image analysis (GEOBIA) and high-spatial resolution GeoEye-1 satellite imagery for three years to map canegrub damage and develop two mapping approaches suitable for risk mapping. The GEOBIA mapping approach for canegrub damage detection was evaluated over three selected study sites in Queensland, covering a total of 254 km² and included five main steps developed in the eCognition Developer software. These included: (1) initial segmentation of sugarcane block boundaries; (2) classification and subsequent omission of fallow/harvested fields, tracks, and other non-sugarcane features within the block boundaries; (3) identification of likely canegrub-damaged areas with low NDVI values and high levels of image texture within each block; (4) the further refining of canegrub damaged areas to low, medium, and high likelihood; and (5) risk classification. The validation based on field observations of canegrub damage at the time of the satellite image capture yielded producer's accuracies between 75% and 98.7%, depending on the study site. Error of commission occurred in some cases due to sprawling, drainage issues, wind, weed, and pig damage. The two developed risk mapping approaches were based on the results of the canegrub damage detection. This research will improve decision making by growers affected by canegrub damage.en
dc.languageenen
dc.publisherTaylor & Francisen
dc.relation.ispartofGIScience and Remote Sensingen
dc.titleUsing GeoEye-1 Imagery for Multi-Temporal Object-Based Detection of Canegrub Damage in Sugarcane Fields in Queensland, Australiaen
dc.typeJournal Articleen
dc.identifier.doi10.1080/15481603.2017.1417691en
dc.subject.keywordsFarming Systems Researchen
dc.subject.keywordsAgronomyen
dc.subject.keywordsSustainable Agricultural Developmenten
local.contributor.firstnameKasperen
local.contributor.firstnameNaderen
local.contributor.firstnameAndrewen
local.contributor.firstnamePeteren
local.contributor.firstnameKeithen
local.contributor.firstnameLisaen
local.contributor.firstnameAllenen
local.contributor.firstnameJillianen
local.subject.for2008070108 Sustainable Agricultural Developmenten
local.subject.for2008070107 Farming Systems Researchen
local.subject.for2008070302 Agronomyen
local.subject.seo2008960403 Control of Animal Pests, Diseases and Exotic Species in Farmland, Arable Cropland and Permanent Cropland Environmentsen
local.subject.seo2008820304 Sugaren
local.profile.schoolSchool of Science and Technologyen
local.profile.emailarobson7@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-20180301-154529en
local.publisher.placeUnited Kingdomen
local.format.startpage285en
local.format.endpage305en
local.identifier.scopusid85038877119en
local.peerreviewedYesen
local.identifier.volume55en
local.identifier.issue2en
local.contributor.lastnameJohansenen
local.contributor.lastnameSallamen
local.contributor.lastnameRobsonen
local.contributor.lastnameSamsonen
local.contributor.lastnameChandleren
local.contributor.lastnameDerbyen
local.contributor.lastnameEatonen
local.contributor.lastnameJenningsen
dc.identifier.staffune-id:arobson7en
local.profile.orcid0000-0001-5762-8980en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:23221en
local.identifier.handlehttps://hdl.handle.net/1959.11/23037en
dc.identifier.academiclevelAcademicen
local.title.maintitleUsing GeoEye-1 Imagery for Multi-Temporal Object-Based Detection of Canegrub Damage in Sugarcane Fields in Queensland, Australiaen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorJohansen, Kasperen
local.search.authorSallam, Naderen
local.search.authorRobson, Andrewen
local.search.authorSamson, Peteren
local.search.authorChandler, Keithen
local.search.authorDerby, Lisaen
local.search.authorEaton, Allenen
local.search.authorJennings, Jillianen
local.uneassociationUnknownen
local.identifier.wosid000427855000008en
local.year.published2018en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/d63c8c14-d096-4a96-ac58-d81c9d1988a1en
local.subject.for2020300210 Sustainable agricultural developmenten
local.subject.for2020300403 Agronomyen
local.subject.seo2020180602 Control of pests, diseases and exotic species in terrestrial environmentsen
local.subject.seo2020260607 Sugaren
dc.notification.tokenb7467698-68ac-436b-86b8-20c744ac6da2en
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School of Science and Technology
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