A Comparison Of Pixel And Object-based Land
Cover Classification: A Case Study Of The
Asmara Region, Eritrea
Author(s)
Y. H. Araya & C. Hergarten
Abstract
In this paper we compare the performance of two image classification paradigms
(object- and pixel-based) for creating a land cover map of Asmara, the capital of
Eritrea and its surrounding areas using a Landsat ETM+ imagery acquired in
January 2000. The image classification methods used were maximum likelihood
for the pixel-based approach and Bhattacharyya distance for the object-oriented
approach available in, respectively, ArcGIS and SPRING software packages.
The advantages and limitations of both approaches are presented and discussed.
The classification outputs were assessed using overall accuracy and Kappa
indices. The pixel- and object-based classification methods result in an overall
accuracy of 78% and 85%, respectively. The Kappa coefficient for pixel- and
object-based approaches was 0.74 and 0.82, respectively. Although the pixelbased
approach is the most commonly used method, assessment and visual
interpretation of the results clearly reveal that the object-oriented approach has
advantages for this specific case-study.
Keywords: Landsat ETM+, land cover, segmentation, pixel- and object-based
classification, accuracy, Kappa coefficient.
1 Introduction
Multi-temporal mapping applying remote sensing and the Geographical
Information System (GIS) are particularly useful for land use management and
Keywords
Landsat ETM+, land cover, segmentation, pixel- and object-basedclassification, accuracy, Kappa coefficient.
Related Book
Other papers in this volume
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