• DocumentCode
    3369694
  • Title

    Models for estimating Leaf Area Index of different crops using hyperspectral data

  • Author

    Dong, Heng ; QIN, Qiming ; You, Lin ; Sui, Xinxin ; Li, Jun ; Jiang, Hongbo ; Wang, Jinliang ; Feng, Haixia ; Sun, Hongmei

  • Author_Institution
    Inst. of Remote Sensing & Geographic Inf. Syst., Peking Univ., Beijing, China
  • fYear
    2010
  • fDate
    25-30 July 2010
  • Firstpage
    3283
  • Lastpage
    3286
  • Abstract
    Leaf Area Index (LAI) is a very important parameter in the area of vegetation quantitative remote sensing. Large range of LAI can reflect the change of eco-system. This article has discussed whether the crop type is a factor to impact the leaf area index retrieval. We choose four types of crops in our research and Hyperspectral Data and leaf area index of these crops were measured. Then the LAI retrieval models were established, which demonstrate the relationships between SVI and LAI. Finally the conclusion can be made that the type of crop is a factor impacting the LAI retrieval. For different crops, the best models are not the same. But the little difference of R2 can be omitted. The SR is the best spectral vegetation index for LAI retrieval.
  • Keywords
    crops; information retrieval; spectral analysis; vegetation mapping; LAI retrieval model; SVI; crop type; crops; hyperspectral data; leaf area index; spectral vegetation index; vegetation quantitative remote sensing; Agriculture; Biological system modeling; Indexes; Reflectivity; Remote sensing; Strontium; Vegetation; Hyperspectral Data; LAI retrieval; Remote sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
  • Conference_Location
    Honolulu, HI
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4244-9565-8
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2010.5653735
  • Filename
    5653735