• DocumentCode
    3381851
  • Title

    Retrieval of grass canopy water content, leaf area index, and dry weight using TM/ETM+ data, a case study in a typical semi-arid steppe in northern china

  • Author

    Wang, Yuanyuan ; Li, Guicai ; Wang, Meng

  • Author_Institution
    Key Lab. of Radiometric Calibration & Validation for Environ. Satellites, China Meteorol. Adm. (LRCVES/CMA), Beijing, China
  • fYear
    2010
  • fDate
    25-30 July 2010
  • Firstpage
    2071
  • Lastpage
    2074
  • Abstract
    In this research, three field surveys were carried out in a typical semi-arid steppe in northern China, respectively on early July, late July and late August in 2008. During each survey, 80 plots established according to the cyclic sampling design were investigated, and three bio-parameters including LAI (Leaf Area Index), CWC (Canopy Water Content) and DW (Dry Weight) were measured. Temporalspecific correlation analysis between TM spectral variables and bio-parameters revealed that the strength of the correlation changed dramatically across time. NDVI was more correlated with CWC and DW in late July, whereas LSWI was a better predictor for CWC and DW in late August. LAI was poorly correlated with TM spectral variables, except in late August. When the three survey datasets were analyzed together, TM band 5 and LSWI were the most suitable for bio-parameters estimation, highlighting the importance of SWIR band in ecological monitoring for semi-arid steppe.
  • Keywords
    ecology; remote sensing; vegetation mapping; AD 2008; ETM+ data; NDVI; TM data; TM spectral variables; bioparameters estimation; cyclic sampling design; dry weight; ecological monitoring; grass canopy water content; leaf area index; northern China; semiarid steppe; temporal-specific correlation analysis; Correlation; Earth; Indexes; Remote sensing; Satellites; Soil; Vegetation; CWC; DW; LAI; TM; semi-arid steppe;
  • 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.2010.5654423
  • Filename
    5654423