Mega city Mexico City is ranked the third largest urban agglomeration to date around the globe. The large extension as
well as dynamic urban transformation and sprawl processes lead to a lack of up-to-date and area-wide data and
information to measure, monitor, and understand the urban situation. This paper focuses on the capabilities of multisensoral
remotely sensed data to provide a broad range of products derived from one scientific field ? remote sensing ?
to support urban managing and planning. Therefore optical data sets from the Landsat and Quickbird sensors as well as
radar data from the Shuttle Radar Topography Mission (SRTM) and the TerraSAR-X sensor are utilised. Using the
multi-sensoral data sets the analysis are scale-dependent. On the one hand change detection on city level utilising the
derived urban footprints enables to monitor and to assess spatiotemporal urban transformation, areal dimension of urban
sprawl, its direction, and the built-up density distribution over time. On the other hand, structural characteristics of an
urban landscape ? the alignment and types of buildings, streets and open spaces ? provide insight in the very detailed
physical pattern of urban morphology on higher scale. The results show high accuracies of the derived multi-scale
products. The multi-scale analysis allows quantifying urban processes and thus leading to an assessment and
interpretation of urban trends.
%0 Conference Paper
%1 dlr59012
%A Taubenböck, Hannes
%A Esch, Thomas
%A Wurm, Michael
%A Thiel, Michael
%A Ullmann, Tobias
%A Roth, Achim
%A Schmidt, Michael
%A Mehl, Harald
%A Dech, Stefan
%B Spie Europe Remote Sensing 2008
%D 2008
%K conference inproceedings lsfe thiel ullmann
%P 1 - 12
%T Urban structure analysis of mega city Mexico City using multisensoral remote sensing data
%U http://elib.dlr.de/59012/
%V Procee
%X Mega city Mexico City is ranked the third largest urban agglomeration to date around the globe. The large extension as
well as dynamic urban transformation and sprawl processes lead to a lack of up-to-date and area-wide data and
information to measure, monitor, and understand the urban situation. This paper focuses on the capabilities of multisensoral
remotely sensed data to provide a broad range of products derived from one scientific field ? remote sensing ?
to support urban managing and planning. Therefore optical data sets from the Landsat and Quickbird sensors as well as
radar data from the Shuttle Radar Topography Mission (SRTM) and the TerraSAR-X sensor are utilised. Using the
multi-sensoral data sets the analysis are scale-dependent. On the one hand change detection on city level utilising the
derived urban footprints enables to monitor and to assess spatiotemporal urban transformation, areal dimension of urban
sprawl, its direction, and the built-up density distribution over time. On the other hand, structural characteristics of an
urban landscape ? the alignment and types of buildings, streets and open spaces ? provide insight in the very detailed
physical pattern of urban morphology on higher scale. The results show high accuracies of the derived multi-scale
products. The multi-scale analysis allows quantifying urban processes and thus leading to an assessment and
interpretation of urban trends.
@inproceedings{dlr59012,
abstract = {Mega city Mexico City is ranked the third largest urban agglomeration to date around the globe. The large extension as
well as dynamic urban transformation and sprawl processes lead to a lack of up-to-date and area-wide data and
information to measure, monitor, and understand the urban situation. This paper focuses on the capabilities of multisensoral
remotely sensed data to provide a broad range of products derived from one scientific field ? remote sensing ?
to support urban managing and planning. Therefore optical data sets from the Landsat and Quickbird sensors as well as
radar data from the Shuttle Radar Topography Mission (SRTM) and the TerraSAR-X sensor are utilised. Using the
multi-sensoral data sets the analysis are scale-dependent. On the one hand change detection on city level utilising the
derived urban footprints enables to monitor and to assess spatiotemporal urban transformation, areal dimension of urban
sprawl, its direction, and the built-up density distribution over time. On the other hand, structural characteristics of an
urban landscape ? the alignment and types of buildings, streets and open spaces ? provide insight in the very detailed
physical pattern of urban morphology on higher scale. The results show high accuracies of the derived multi-scale
products. The multi-scale analysis allows quantifying urban processes and thus leading to an assessment and
interpretation of urban trends.},
added-at = {2015-10-29T10:39:25.000+0100},
author = {Taubenb{\"o}ck, Hannes and Esch, Thomas and Wurm, Michael and Thiel, Michael and Ullmann, Tobias and Roth, Achim and Schmidt, Michael and Mehl, Harald and Dech, Stefan},
biburl = {https://www.bibsonomy.org/bibtex/28f61190b380f6402ce2f8b4d1fcd04d8/mschramm},
booktitle = {Spie Europe Remote Sensing 2008},
interhash = {8de7ff743ab356baa46fcc442c324666},
intrahash = {8f61190b380f6402ce2f8b4d1fcd04d8},
keywords = {conference inproceedings lsfe thiel ullmann},
month = {September},
pages = {1 - 12},
timestamp = {2019-06-06T09:41:48.000+0200},
title = {Urban structure analysis of mega city Mexico City using multisensoral remote sensing data},
url = {http://elib.dlr.de/59012/},
volume = {Procee},
year = 2008
}