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Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery


Jebur, Mustafa Neamah and Mohd Shafri, Helmi Zulhaidi and Pradhan, Biswajeet and Tehrany, Mahyat Shafapour (2014) Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery. Geocarto International, 29 (7). 792-806. ISSN 1010-6049; ESSN: 1752-0762


To have sustainable management and proper decision-making, timely acquisition and analysis of surface features are necessary. Traditional pixel-based analysis is the popular way to extract different categories, but it is not comparable by the achievements that can be achieved through the object-based method that uses the additional characteristics of features in the process of classification. In this paper, three types of classification were used to classify SPOT 5 satellite image in mapping land cover; Support vector machine (SVM) pixel-based, SVM object-based and Decision Tree (DT) pixel-based classification. Normalised Difference Vegetation Index and the brightness value of two infrared bands (NIR and SWIR) were used in manually developed DT classification. The classification of the SVM (pixel based) was generated using the selected groups of pixels that represent the selected features. In addition, the SVM (object based) was implemented by using radial-based function kernel. The classified features were oil palm, rubber, urban area, soil, water and other vegetation. The study found that the overall classification of the DT was the lowest at 69.87% while those of SVM (pixel based) and SVM (object based) were 76.67 and 81.25%, respectively.

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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.1080/10106049.2013.848944
Publisher: Taylor & Francis
Keywords: LULC; Pixel based; Object based; Classification; GIS; Remote sensing; SPOT 5
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 23 Dec 2015 07:17
Last Modified: 23 Dec 2015 07:17
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1080/10106049.2013.848944
URI: http://psasir.upm.edu.my/id/eprint/34884
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