• DocumentCode
    2705824
  • Title

    Remote sensing, crop yield estimation and agricultural vulnerability assessment: A case of Southern Alberta

  • Author

    Xu, Wei ; Ren, Xiaomeng ; Smith, Anne

  • Author_Institution
    Dept. of Geogr., Univ. of Lethbridge, Lethbridge, AB, Canada
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    This research investigates the relationship between agricultural production and the occurrence of meteorological droughts over time. A remote sensing approach is developed to estimate the yield of cereal crops based on the remotely sensed data in the study area. The yield estimates from remotely sensed imageries provide a primary data source to measure agricultural well-being and quantify agricultural vulnerability to drought. The drought condition as the stressor to agricultural production systems is characterized using the standard precipitation index (SPI). The results of the study indicate that crop production system in Southern Alberta is very vulnerable to drought. About half of the study area is associated with a high to extremely high vulnerability. If the drought trend in the recent past repeats itself in the near further, it can be expected that crop production in these areas will be seriously threatened.
  • Keywords
    agriculture; crops; hydrological techniques; hydrology; rain; vegetation mapping; Canada; SPI; agricultural drought vulnerability quantification; agricultural production systems; agricultural vulnerability assessment; agricultural well being quantification; cereal crop yield estimation; meteorological droughts; primary data source; remote sensing approach; southern Alberta; standard precipitation index; Irrigation; Production; Remote sensing; Satellites; Sensitivity; Yield estimation; Agricultural volnerability; crop yield; drought; remote sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics, 2011 19th International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2161-024X
  • Print_ISBN
    978-1-61284-849-5
  • Type

    conf

  • DOI
    10.1109/GeoInformatics.2011.5980692
  • Filename
    5980692