Object-based image information fusion using multisensor earth observation data over urban areas
Publikation aus Digital
Univ.-Prof. Dipl.-Forstw. Dr. Mathias Schardt, Thomas Esch and Stefan Dech
International Journal of Image and Data Fusion , 1/2011
At present, the majority of the world's population is living in urban areas. Cities undergo constant development in their morphology. The latter is always a turnedinto- stone representation of the coetaneous social, economical and technical values. The technical developments in recent years of very high-resolution spaceborne earth observation methods enable mapping of large urban areas with a decent level of detail. Additionally, detailed elevation information of urban areas in developed countries is widely available. Digital surface models (DSMs) support the classification of urban structures beyond two-dimensional classifications. We present a hierarchical, object-based and transferable framework to extract the urban structure on a high level of geometric detail for two test sites in Germany. The results show accuracies of above 90% for the land-use/land-cover classification for both test sites applying the same routines. DSMs from various sources have been utilised for the extraction of the individual building structures with accuracies of 90% and 80%, respectively. The methodology is suited to extract the urban structure on the level of individual buildings and the results can be utilised as 3D city model for the purpose of decision-making, urban planning and further analyses.