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Menschen zählen aus dem All. Möglichkeiten und Grenzen von Satellitendaten zur Abschätzung der Bevölkerungsentwicklung und des Gebäudebestandes in deutschen Städten

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Author Info

  • Michael Wurm
  • Hannes Taubenböck
  • Jan Goebel
  • Stefan Dech
  • Gert G. Wagner

Abstract

Is it possible to count the earth’s population from outer space? The answer is yes, in urban areas it is possible. However, this can only be done in an indirect manner: by identifying physical objects in the urban landscape in earth observation data and using these to estimate the number of inhabitants. Since the approach is indirect, data protection and the individual right to privacy are fully guaranteed. The data obtained using this method fill a gap, given that municipal population registers do not contain accurate population counts. However, remote sensing technology is not able to provide cadastral information. Nevertheless, as this paper shows, satellite imagery is capable of providing the basis for population estimates for small-scale areas. And, of course, remote sensing data also can be used to estimate the building stock. It would make sense to produce such estimates during the intervals between each building stock census, which is usually conducted every ten years with the population census. Remote sensing data cannot replace a population census, but can enrich the analytical power of population census data.

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File URL: http://www.ratswd.de/download/RatSWD_WP_2010/RatSWD_WP_155.pdf
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Bibliographic Info

Paper provided by German Council for Social and Economic Data (RatSWD) in its series Working Paper Series of the German Council for Social and Economic Data with number 155.

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Length: 23
Date of creation: 2010
Date of revision:
Handle: RePEc:rsw:rswwps:rswwps155

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Related research

Keywords: Remote Sensing; spatial disaggregation; population estimation; census;

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  1. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2009. "Measuring Economic Growth from Outer Space," NBER Working Papers 15199, National Bureau of Economic Research, Inc.
  2. Xi Chen & William D. Nordhaus, 2010. "The Value of Luminosity Data as a Proxy for Economic Statistics," Cowles Foundation Discussion Papers 1766, Cowles Foundation for Research in Economics, Yale University.
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