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Exploring the Linkage of Spatial Indicators from Remote Sensing Data with Survey Data: The Case of the Socio-Economic Panel (SOEP) and 3D City Models

Author

Listed:
  • Jan Goebel
  • Michael Wurm
  • Gert G. Wagner

Abstract

This paper demonstrates the spatial evaluation of survey data from the German Socio-Economic Panel (SOEP) study using geo-coordinates and spatially relevant indicators from remote sensing data. By geocoding the addresses of survey households with block-level geographic precision (while preventing their identification by name and guaranteeingtheir complete anonymity), data on SOEP respondents can now be analyzed in a specific spatial context. In the past, regional analyses of SOEP based on official regional indicators (e.g., the unemployment rate) always had only very imprecise spatial information to work with. This limitation has now been overcome with the geocoded respondents' information. Within a protected unit of the fieldwork organization responsible for SOEP (TNS Infratest, Munich), the addresses of survey households can now be used to generate a variable describing the location of the household with block-level precision. At DIW Berlin, this additional variable is fed into a special computer infrastructure with multiple security layers that makes the socio-economic analysis possible. This paper demonstrates the use of this geographicallocation and remote sensing data to check respondents' subjective assessments of the location of their residence, anddiscusses the analytical potential of linking remote sensing data and survey data.

Suggested Citation

  • Jan Goebel & Michael Wurm & Gert G. Wagner, 2010. "Exploring the Linkage of Spatial Indicators from Remote Sensing Data with Survey Data: The Case of the Socio-Economic Panel (SOEP) and 3D City Models," SOEPpapers on Multidisciplinary Panel Data Research 283, DIW Berlin, The German Socio-Economic Panel (SOEP).
    • Handle: RePEc:diw:diwsop:diw_sp283
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    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.354340.de/diw_sp0283.pdf
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    References listed on IDEAS

    as
    1. Peter Hintze & Tobia Lakes, 2009. "Geographically Referenced Data for Social Science," RatSWD Working Papers 125, German Data Forum (RatSWD).
    2. Denis Gerstorf & Nilam Ram & Jan Goebel & Jürgen Schupp & Ulman Lindenberger & Gert G. Wagner, 2010. "Where People Live and Die Makes a Difference: Individual and Geographic Disparities in Well-Being Progression at the End of Life," SOEPpapers on Multidisciplinary Panel Data Research 287, DIW Berlin, The German Socio-Economic Panel (SOEP).
    3. Gert G. Wagner & Joachim R. Frick & Jürgen Schupp, 2007. "The German Socio-Economic Panel Study (SOEP) – Scope, Evolution and Enhancements," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 127(1), pages 139-169.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Remote sensing data; social sciences; behavioral sciences; multi-disciplinarity; SOEP;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns

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