• DocumentCode
    2327742
  • Title

    Deriving economic and social indicators from imagery

  • Author

    Irvine, James ; Lepanto, Janet ; Regan, John ; Young, Michelle

  • Author_Institution
    Draper Lab., Cambridge, MA, USA
  • fYear
    2012
  • fDate
    9-11 Oct. 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The application of remote sensing to the social sciences is an emerging research area. People´s behavior and values shape the environment in which they live. Similarly, values and behaviors are influenced by the environment. This study explores the relationship between features observable in overhead imagery and direct measurements of attitudes obtained through surveys. We focus on three topic areas: (1) Income and Economic Development (2) Centrality and Decision Authority (3) Social Capital Using commercial satellite imagery data from rural Afghanistan, we present an exploration of the direct and indirect indicators derived from the imagery. We demonstrate a methodology for extracting relevant measures from the imagery, using a combination of human-guided and automated methods. These imagery observables indicate characteristics of the villages which will be compared to survey data in future modeling work. Preliminary survey modeling, based on data from sub-Saharan Africa, suggests that modeling of the Afghan data will also demonstrate a relationship between remote sensing data and survey-based measures of economic and social phenomena. We conclude with a discussion of the next steps, which include extensions to new regions of the world.
  • Keywords
    attitude measurement; economic indicators; geophysical image processing; remote sensing; social sciences; Afghan data; automated methods; centrality authority; commercial satellite imagery data; decision authority; direct attitudes measurements; economic indicators; human-guided methods; overhead imagery; remote sensing application; rural Afghanistan; social capital; social indicators; social sciences; subSaharan Africa; survey-based measures; villages characteristics; economic indicators; governance; imagery; remote sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Imagery Pattern Recognition Workshop (AIPR), 2012 IEEE
  • Conference_Location
    Washington, DC
  • ISSN
    1550-5219
  • Print_ISBN
    978-1-4673-4558-3
  • Type

    conf

  • DOI
    10.1109/AIPR.2012.6528213
  • Filename
    6528213