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dc.contributor.authorAlston-Knox, Clair L
dc.contributor.authorMengersen, Kerrie L
dc.contributor.authorDenham, Robert
dc.contributor.authorStrickland, Christopher M
dc.date.accessioned2018-03-12T12:30:32Z
dc.date.available2018-03-12T12:30:32Z
dc.date.issued2018
dc.identifier.issn1387-3547
dc.identifier.doi10.1007/s10530-017-1631-x
dc.identifier.urihttp://hdl.handle.net/10072/369693
dc.description.abstractThis paper presents a Bayesian mixture model approach for detecting areas of habitat that are suitable for S. invicta infestation, aiding the ongoing surveillance for early detection of these exotic pests. We show that Landsat imagery is an affordable and valuable tool to assist in determining an informed surveillance strategy. In this paper, we use Landsat band 3 (visible red), Landsat band 6 (mid infrared) and a soil brightness index, in various combinations, to assess the probability that the area associated with each pixel is habitable terrain, either in a multivariate analysis, or as a univariate spatial temporal model. The multivariate analysis allows researchers to create meaningful clusters that reflect the sometimes complex combinations of conditions of conditions that form suitable habitat, rather then relying on single derived indices.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofpagefrom1
dc.relation.ispartofpageto19
dc.relation.ispartofjournalBiological Invasions
dc.subject.fieldofresearchEnvironmental sciences
dc.subject.fieldofresearchBiological sciences
dc.subject.fieldofresearchOther biological sciences not elsewhere classified
dc.subject.fieldofresearchcode41
dc.subject.fieldofresearchcode31
dc.subject.fieldofresearchcode319999
dc.titleModelling habitat and planning surveillance using Landsat imagery: a case study using Imported Red Fire ants
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Health, School of Applied Psychology
gro.description.notepublicThis publication has been entered into Griffith Research Online as an Advanced Online Version.
gro.hasfulltextNo Full Text
gro.griffith.authorAlston-Knox, Clair L.


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