• DocumentCode
    3071558
  • Title

    Identification of agricultural crops in early stages using remote sensing images

  • Author

    Valero, S. ; Ceccato, Pietro ; Baethgen, Walter E. ; Chanussot, Jocelyn

  • Author_Institution
    CESBIO - CNES, Univ. de Toulouse, Toulouse, France
  • fYear
    2013
  • fDate
    21-26 July 2013
  • Firstpage
    4229
  • Lastpage
    4232
  • Abstract
    Real-time monitoring of agricultural crops is increasingly important because of the involved huge economic impact. The automatic identification of crops, as early as possible during the agricultural season, is an important issue supporting agricultural policies. In this context, the objective of this article is to evaluate the possibilities of remote sensing data to identify corn and soybean crops in the early growing season. The proposed study evaluates the potential of hyperspectral data and multispectral NDVI times series. Experimental results illustrate the challenges of crop detection in early stages.
  • Keywords
    crops; remote sensing; time series; vegetation mapping; agricultural crop identification; agricultural crop real-time monitoring; agricultural policies; agricultural season; automatic crop identification; corn crop identification; crop detection challenges; early growing season; early stages; huge economic impact; hyperspectral data potential; multispectral NDVI time series; remote sensing data; remote sensing images; soybean crop identification; Agriculture; Hyperspectral imaging; MODIS; Spatial resolution; Time series analysis; NDVI times series; crop monitoring; hyperspectral imagery;
  • 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.2013.6723767
  • Filename
    6723767