Capacities of Remote Sensing for Population Estimation in Urban Areas

  • Julia KubanekEmail author
  • Eike-Marie Nolte
  • Hannes Taubenböck
  • Friedemann Wenzel
  • Martin Kappas
Part of the Environmental Hazards book series (ENHA)


In the past few decades, devastating earthquakes have caused high social and economic losses in cities. Earthquakes cannot be avoided, but the devastating impacts, especially fatalities, can be minimized through pre-event emergency response planning and preparedness. The development of emergency plans strongly relies on up-to-date population and inventory data. However, existing techniques for population data generation do not meet the requirements of many of today’s dynamic cities. In this context, the importance of remote sensing as a cutting-edge technology for data acquisition in urban areas is increasing. The present study analyzes the capacities and limitations of high resolution optical satellite imagery (IKONOS) for modeling population distribution in the district of Zeytinburnu in Istanbul, Turkey. The results show remote sensing to be an independent, up-to-date and area-wide data source. The use of remote sensing facilitates a mechanism to provide necessary quantitative information on urban morphology and population distribution in a fast and accurate way. The generated data do not have the quality of cadastral data sets but they meet the requirements of identifying bottlenecks, highly risky zones, etc. and can serve as a base for decision making.


Buildings (built-up area, floor numbers, inventory, occupancy, residential living space, usable space) Earthquakes Geographic Information System (GIS) IKONOS Istanbul Population Spatial distribution Modeling Remote sensing Satellite imagery Urban areas Zeytinburnu 



The present study was developed in a cooperation of the Center for Disaster Management and Risk Reduction Technology (CEDIM) at the Karlsruhe Institute of Technology (KIT), the Cartography, GIS and Remote Sensing Section of the Institute of Geography at the University of Göttingen, Germany and the German Remote Sensing Data Center (DFD) at the German Aerospace Center (DLR).

We gratefully acknowledge the support of Mustafa Erdik, Tamer Soylu, and Dietmar Borst for providing comprehensive data on Istanbul. Special thanks go to James Daniell and the anonymous reviewers for their extensive professional comments that helped to improve the manuscript.


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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Julia Kubanek
    • 1
    Email author
  • Eike-Marie Nolte
    • 4
  • Hannes Taubenböck
    • 3
  • Friedemann Wenzel
    • 5
  • Martin Kappas
    • 2
  1. 1.Geodetic Institute (GIK)Karlsruhe Institute of Technology (KIT)KarlsruheGermany
  2. 2.Institute of GeographyUniversity of GöttingenGöttingenGermany
  3. 3.Georisks and Civil SecurityGerman Remote Sensing Data Center (DFD) German Aerospace Center (DLR)WesslingGermany
  4. 4.Universitätsrechenzentrum (URZ)Heidelberg UniversityHeidelbergGermany
  5. 5.Geophysical Institute (GPI)Karlsruhe Institute of Technology (KIT)KarlsruheGermany

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