Quantification of urban structure on building block level utilizing multisensoral remote sensing data

Michael Wurm; Hannes Taubenböck; Stefan Dech

doi:10.1117/12.864930

25 October 2010 Quantification of urban structure on building block level utilizing multisensoral remote sensing data

Michael Wurm, Hannes Taubenböck, Stefan Dech

Proceedings Volume 7831, Earth Resources and Environmental Remote Sensing/GIS Applications; 78310H (2010) https://doi.org/10.1117/12.864930
Event: SPIE Remote Sensing, 2010, Toulouse, France

Abstract

Dynamics of urban environments are a challenge to a sustainable development. Urban areas promise wealth, realization of individual dreams and power. Hence, many cities are characterized by a population growth as well as physical development. Traditional, visual mapping and updating of urban structure information of cities is a very laborious and cost-intensive task, especially for large urban areas. For this purpose, we developed a workflow for the extraction of the relevant information by means of object-based image classification. In this manner, multisensoral remote sensing data has been analyzed in terms of very high resolution optical satellite imagery together with height information by a digital surface model to retrieve a detailed 3D city model with the relevant land-use / land-cover information. This information has been aggregated on the level of the building block to describe the urban structure by physical indicators. A comparison between the indicators derived by the classification and a reference classification has been accomplished to show the correlation between the individual indicators and a reference classification of urban structure types. The indicators have been used to apply a cluster analysis to group the individual blocks into similar clusters.

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Michael Wurm, Hannes Taubenböck, and Stefan Dech "Quantification of urban structure on building block level utilizing multisensoral remote sensing data", Proc. SPIE 7831, Earth Resources and Environmental Remote Sensing/GIS Applications, 78310H (25 October 2010); https://doi.org/10.1117/12.864930

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