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Examples of object-oriented classification performed on high-resolution satellite images

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Lewiński S., Zaremski K., Kwiatkowska J. M.

Miscellanea Geographica. Regional Studies on Development

2004

vol. 11

349-358

Information about the types of land cover and its use is obtained by the visual interpretation of the color composite of satellite images or by the use of automatic classification algorithms. For obvious reasons, the automatic classification methods make it possible to obtain information quicker and much faster than the traditional interpretation method. The commonly used automatic methods of satellite image classification, based on supervised or unsupervised classification algorithms, are the most accurate when used with low resolution images. In the case of images with 1-meter-sized pixels, showing a diversity of land cover forms, it is not possible to obtain satisfactory results. New classification techniques, based on object-oriented classification algorithms, have been developing for a couple of years now. In contrast to the traditional methods, the new operating procedure does not involve the classification of single pixels, but of entire objects, into which the content of the satellite image is divided. Aside from the spectral values of the pixels, the shape of the objects created by the pixels and the relationships between the objects, are also considered during the analysis. Similar to visual interpretation, variation in the texture of the image can also be taken into account in this case. The aim of this article is to present the possibility of using high density satellite images in object-oriented classification. The classification presented is that of a high-rise built area in Wrocław and of bridges on the Vistula River in Warsaw.

Differentiation between forms of urban development using the object-oriented classification method with Central Warsaw as the example

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Zaremski K., Szmajda D.

Miscellanea Geographica. Regional Studies on Development

2006

vol. 12

315-327

The aim of the paper is to present automated methods of discrimination of urban development forms using object-oriented classification in high-resolution images taken by the Ikonos satellite. The object-oriented classification makes possible to describe individual classes using not only the spectral reflection values but also the shapes, textures and topology of objects. The classification process as such is based on the theory of fuzzy sets. The research covered an area of 25 km,., situated in central Warsaw. As a result of object-oriented classification, five classes of development typical of large cities were distinguished and described.

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2 Miscellanea Geographica. Regional Studies on Development

2 Zaremski K.

1 Kwiatkowska J. M.

1 Lewiński S.

1 Szmajda D.

1 2006

1 2004

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Examples of object-oriented classification performed on high-resolution satellite images

Differentiation between forms of urban development using the object-oriented classification method with Central Warsaw as the example