• DocumentCode
    2140347
  • Title

    Relationship between leaf area index and proper vegetation indices across a wide range of cultivars

  • Author

    Tan, Changwei ; Huang, Wenjiang ; Liu, Liangyun ; Wang, Jihua ; Zhao, Chunjiang

  • Author_Institution
    Nat. Eng. Res. Center for Inf. Technol. in Agric., Beijing
  • Volume
    6
  • fYear
    2004
  • fDate
    20-24 Sept. 2004
  • Firstpage
    4070
  • Abstract
    There is considerable interest in assessing leaf area index (LAI) to evaluate crop growth and production. In this article, an operational approach was proposed to evaluating LAI of summer maize for different cultivars under different nitrogen treatments and developmental stages by selecting ten familiar remote sensing vegetation indices (VIs). The result indicated that VIs had the potential for faithfully estimating LAI, and the estimation power of VIs for assessing LAI was best from bell stage to silking stage, which primarily depended on the LAI dynamic variation during the process of the growth. When the estimation power of VIs was systematically verified with the other independent data set, the VIs could accurately evaluate LAI. The ratio spectral index of R810 /R560 was the best index to estimate LAI, which was wondrously sensitive to LAI dynamic variation almost without the influence of cultivars, growth stages and nitrogen treatments. The exponential regression model for LAI based on R810/R560 was also established with a mean determination of coefficient (R 2) of 0.9573 (P value=0.01) and a mean root mean square error (RAISE) of 0.0365. Therefore, the spectral index of R810/R 560 could be considered as a sensitive indicator as LAI of summer maize
  • Keywords
    agriculture; crops; mean square error methods; regression analysis; vegetation mapping; crop growth; crop production; cultivars; exponential regression model; leaf area index; mean root mean square error; nitrogen treatments; proper vegetation indices; ratio spectral index; remote sensing vegetation indices; sensitive indicator; summer maize; Agricultural engineering; Agriculture; Area measurement; Crops; Extraterrestrial measurements; Information technology; Nitrogen; Reflectivity; Soil; Vegetation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    0-7803-8742-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.2004.1370025
  • Filename
    1370025