Full metadata record
DC FieldValueLanguage
dc.contributorFaculty of Construction and Environmenten_US
dc.contributor.advisorWong, Man Sing Charles (LSGI)-
dc.creatorHu, Jinyuan-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/8331-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleDevelopment of high resolution satellite image classification method in land use and land cover mappingen_US
dcterms.abstractAs the development of remote sensing technology in land use and land cover mapping, classification method of high resolution satellite image has become more and more important and popular in the application. As one of the most important technique of accuracy improvement, multiple classifier systems (MCS) not only attract increasing interest in the field of remote sensing image classification, but also become hot topics in pattern recognition and machine learning. In this thesis, Satellite Pour 1' Observation de la Terre (SPOT) VI multi-spectral satellite images are applied and classified into 8 land cover classes using four base classifiers, they are maximum likelihood classifier, neural network classifier, Mahalanobis distance classifier and minimum distance classifier. These four classifiers are trained using the same data sets. The prior probability and the a posteriori probability are derived from the confusion matrices of those classifiers, which are produce accuracy and user accuracy respectively. A multiple classifier system is designed in this thesis to combine these classifiers to improve the accuracy of the classification result.en_US
dcterms.extentviii, 87 page : color illustrationsen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2015en_US
dcterms.educationalLevelAll Masteren_US
dcterms.educationalLevelM.Sc.en_US
dcterms.LCSHRemote-sensing images.en_US
dcterms.LCSHRemote sensing -- Data processing.en_US
dcterms.LCSHImage processing.en_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsrestricted accessen_US

Files in This Item:
File Description SizeFormat 
b2831542x.pdfFor All Users (off-campus access for PolyU Staff & Students only)2.9 MBAdobe PDFView/Open


Copyright Undertaking

As a bona fide Library user, I declare that:

  1. I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
  2. I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
  3. I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.

By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.

Show simple item record

Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/8331