Sensitivity analysis of a decision tree classification to input data errors using a general Monte Carlo error sensitivity model

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dc.contributor.authorHuang, Zhi
dc.contributor.authorLaffan, Shawn
dc.date.accessioned2015-12-10T22:39:47Z
dc.date.issued2009
dc.date.updated2016-02-24T10:50:55Z
dc.description.abstractWe analysed the sensitivity of a decision tree derived forest type mapping to simulated data errors in input digital elevation model (DEM), geology and remotely sensed (Landsat Thematic Mapper) variables. We used a stochastic Monte Carlo simulation model
dc.identifier.issn1365-8816
dc.identifier.urihttp://hdl.handle.net/1885/57334
dc.publisherTaylor & Francis Group
dc.sourceInternational Journal of Geographical Information Science
dc.subjectKeywords: digital elevation model; error analysis; Gaussian method; land cover; land use; Landsat; Monte Carlo analysis; sensitivity analysis; terrain; uncertainty analysis; vegetation mapping Error modelling; Land use and land cover; Terrain analysis; Vegetation mapping and modelling
dc.titleSensitivity analysis of a decision tree classification to input data errors using a general Monte Carlo error sensitivity model
dc.typeJournal article
local.bibliographicCitation.issue11
local.bibliographicCitation.lastpage1452
local.bibliographicCitation.startpage1433
local.contributor.affiliationHuang, Zhi, College of Medicine, Biology and Environment, ANU
local.contributor.affiliationLaffan, Shawn, University of New South Wales
local.contributor.authoremailrepository.admin@anu.edu.au
local.contributor.authoruidHuang, Zhi, u4026175
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor040699 - Physical Geography and Environmental Geoscience not elsewhere classified
local.identifier.absfor080109 - Pattern Recognition and Data Mining
local.identifier.ariespublicationU4279067xPUB396
local.identifier.citationvolume23
local.identifier.doi10.1080/13658810802634949
local.identifier.scopusID2-s2.0-70350779978
local.identifier.uidSubmittedByU4279067
local.type.statusPublished Version

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