Object-based classification algorithms for mapping
dc.contributor.advisor
Stuart, Neil
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dc.contributor.author
Reyes Firpo, Patricia
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dc.date.accessioned
2008-08-20T10:35:33Z
dc.date.available
2008-08-20T10:35:33Z
dc.date.issued
2008-12-05
dc.description.abstract
An adequate maintenance and protection of urban green spaces requires update and accurate information of these features. Remote sensing techniques provide an important source of information to automate urban land-cover mapping.
Nevertheless, some techniques tend to be more appropriate than others in distinguishing specific categories, such as vegetation, particularly when classifying high resolution imagery in urban environments. Previous studies have shown that the conventional pixel by pixel classification cannot obtain very satisfactory results in urban spaces whereas an Object-Oriented approach tends to achieved better results (e.g. Laliberte et al., 2007, Cleve et al., 2008). This paper aims to assess the suitability and effectiveness of using object-based classification of high resolution Ikonos imagery to map and resolve different types of green spaces in the city of Kuala Lumpur. A set of fuzzy membership rules was developed within a training subset of IKONOS imagery for identifying four land-cover classes in different segmentation levels. Focus was placed on the vegetation class. The classification result for the vegetation class yielded to producer’s accuracies higher than 64% and user’s accuracies higher than 90%, suggesting that this is an efficient approach to deal with the spatial and spectral variability of urban environment to map general vegetation spaces. However improvement is needed in order to discriminate between different vegetation types and qualities.
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6129664 bytes
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3414744 bytes
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982370 bytes
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dc.format.mimetype
application/pdf
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dc.format.mimetype
application/pdf
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application/pdf
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dc.identifier.uri
http://hdl.handle.net/1842/2473
dc.language.iso
en
dc.publisher
The University of Edinburgh
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dc.subject
object-oriented classification
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dc.subject
eCognition
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dc.subject
urban green spaces
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dc.subject
Kuala Lumpur
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dc.subject
GIS
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dc.subject
MSc by Research in GIS
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dc.title
Object-based classification algorithms for mapping
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Masters
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dc.type.qualificationname
MSc(R) Master of Science by Research
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dcterms.accessRights
RESTRICTED ACCESS
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