%0 Conference Paper %1 dlr66290 %A Wurm, Michael %A Taubenböck, Hannes %A Dech, Stefan %B SPIE Europe Remote Sensing 2010 %D 2010 %K conference inproceedings Dech %P 1-12 %T Quantification of urban structure on building block level utilizing multisensoral remote sensing data. %U http://elib.dlr.de/66290/ %X 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.

@inproceedings{dlr66290, 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.}, added-at = {2020-09-11T12:04:50.000+0200}, author = {Wurm, Michael and Taubenb{\"o}ck, Hannes and Dech, Stefan}, biburl = {https://www.bibsonomy.org/bibtex/250c68690cfd5db93c8641dc3ff752cd5/earthobs_uniwue}, booktitle = {SPIE Europe Remote Sensing 2010}, interhash = {96f229c2405f4c829393f0527052b5d5}, intrahash = {50c68690cfd5db93c8641dc3ff752cd5}, keywords = {conference inproceedings Dech}, month = {Dezember}, pages = {1-12}, timestamp = {2020-10-29T09:22:08.000+0100}, title = {Quantification of urban structure on building block level utilizing multisensoral remote sensing data.}, url = {http://elib.dlr.de/66290/}, year = 2010 }