Object-oriented classification of land use in urban areas applying very high resolution satellite data
Project Leader: Dr. Klaus Steinnocher
PhD Thesis T. BAUER - Technical University Vienna
Beginning: 10.1997
End: 07.2001
The availability of the new very high resolution satellite
imagery will offer a wide range of new applications in the field of remote sensing. These
image data sets will facilitate for the first time the potential to map urban areas at a
spatial scale previously unattainable. Due to its complex structures the analysis of urban
areas will highly profit from the advanced sensors with a spatial resolution of less than
5 meters. Information about actual land use is an important task for the management and
planning in urban areas. The traditional method to gain this information is based on the
visual interpretation of aerial photographs. High resolution satellite data will be an
alternative for updating and maintaining cartographic and geographic databases at reduced
costs.
To take full benefit of the potential of these data new processing techniques have to be
applied. The aim of the research is to formalise the visual interpretation procedure in
order to automate the whole process. The assumption underlying this approach is that the
land use functions can be distinguished on the basis of the differences in spatial
distribution and pattern of land cover forms. Therefore a two-stage classification
procedure is applied. In a first stage a land cover map is produced. In a second stage the
morphological properties and spatial patterns of the land cover objects are analysed with
the Structural Analysing and Mapping System leading to a characterisation and description
of distinct urban land use categories. This information is then used for building a rule
system that is implemented in a new commercial software tool called eCognition. An
object-oriented classifier applies the rules to the land cover objects resulting in the
required land use map. The potential of this method is demonstrated in a case study using
IKONOS data covering a part of the metropolitan area of Vienna.