Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/3044
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dc.contributor.authorSchmidt, K Sen
dc.contributor.authorSkidmore, A Ken
dc.contributor.authorKloosterman, E Hen
dc.contributor.authorvan Oosten, Hen
dc.contributor.authorKumar, Laliten
dc.contributor.authorJanssen, J A Men
dc.date.accessioned2009-11-12T16:31:00Z-
dc.date.issued2004-
dc.identifier.citationPhotogrammetric Engineering and Remote Sensing, 70(6), p. 703-715en
dc.identifier.issn0099-1112en
dc.identifier.urihttps://hdl.handle.net/1959.11/3044-
dc.description.abstractMapping and monitoring saltmarshes in the Netherlands are important activities of the Ministry of Public Works (Rijkswaterstaat). The Survey Department (Meetkundige Dienst) produces vegetation maps using aerial photographs. However, it is a time-consuming and expensive activity. The accuracy of the conventional vegetation map derived from using aerial photograph interpretation (API) is estimated to be around 43%. In this study, an alternative method is demonstrated that uses an expert system to combine airborne hyperspectral imagery with terrain data derived from radar altimetry. The accuracy of the vegetation map generated by the expert system increased to 66 percent. When hyperspectral imagery alone was used to classify coastal wetlands, an accuracy of 40 percent was achieved - comparable to the accuracy of the API-derived vegetation map. An analysis of the efficiency of the proposed expert system showed that the speed of map production is increased by using the new method. This means that digital image classification using the expert system is an objective and repeatable method superior to the conventional API method.en
dc.languageenen
dc.publisherAmerican Society for Photogrammetry and Remote Sensingen
dc.relation.ispartofPhotogrammetric Engineering and Remote Sensingen
dc.titleMapping Coastal Vegetation Using an Expert System and Hyperspectral Imageryen
dc.typeJournal Articleen
dc.subject.keywordsEnvironmental Technologiesen
local.contributor.firstnameK Sen
local.contributor.firstnameA Ken
local.contributor.firstnameE Hen
local.contributor.firstnameHen
local.contributor.firstnameLaliten
local.contributor.firstnameJ A Men
local.subject.for2008090703 Environmental Technologiesen
local.subject.seo2008960902 Coastal and Estuarine Land Managementen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.emaillkumar@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordpes:1772en
local.publisher.placeUnited States of Americaen
local.format.startpage703en
local.format.endpage715en
local.peerreviewedYesen
local.identifier.volume70en
local.identifier.issue6en
local.contributor.lastnameSchmidten
local.contributor.lastnameSkidmoreen
local.contributor.lastnameKloostermanen
local.contributor.lastnamevan Oostenen
local.contributor.lastnameKumaren
local.contributor.lastnameJanssenen
dc.identifier.staffune-id:lkumaren
local.profile.orcid0000-0002-9205-756Xen
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:3126en
dc.identifier.academiclevelAcademicen
local.title.maintitleMapping Coastal Vegetation Using an Expert System and Hyperspectral Imageryen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.relation.urlhttp://www.asprs.org/publications/pers/2004journal/june/abstracts.html#703en
local.search.authorSchmidt, K Sen
local.search.authorSkidmore, A Ken
local.search.authorKloosterman, E Hen
local.search.authorvan Oosten, Hen
local.search.authorKumar, Laliten
local.search.authorJanssen, J A Men
local.uneassociationUnknownen
local.year.published2004en
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