• DocumentCode
    3070218
  • Title

    Remote sensing and crowd-sourcing

  • Author

    Guida, Raffaella ; Brett, Peter T. B. ; Khan, Shabia Shabir

  • Author_Institution
    Surrey Space Centre, Univ. of Surrey, Guildford, UK
  • fYear
    2013
  • fDate
    21-26 July 2013
  • Firstpage
    3942
  • Lastpage
    3945
  • Abstract
    Collection of ground truth to validate remote sensing classification and/or detection algorithms is rarely accounted for due to the inaccessibility of the sites or the elevated costs of such operations. In this paper some of the opportunities behind crowd-sourcing are explored through the description of a remote sensing project on water quality monitoring in Africa where the ground truth was collected involving and training people from local communities.
  • Keywords
    environmental monitoring (geophysics); geophysical image processing; image classification; remote sensing; water quality; Africa; crowd sourcing; remote sensing classification algorithms; remote sensing detection algorithms; remote sensing project; water quality monitoring; Data processing; Diseases; Educational institutions; Indexes; Lakes; Monitoring; Remote sensing; crowd-sourcing; water quality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
  • Conference_Location
    Melbourne, VIC
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4799-1114-1
  • Type

    conf

  • DOI
    10.1109/IGARSS.2013.6723695
  • Filename
    6723695