• Title of article

    Vegetation water content estimation for corn and soybeans using spectral indices derived from MODIS near- and short-wave infrared bands

  • Author/Authors

    Chen، نويسنده , , Daoyi and Huang، نويسنده , , Jingfeng and Jackson، نويسنده , , Thomas J.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2005
  • Pages
    12
  • From page
    225
  • To page
    236
  • Abstract
    The estimation of vegetation water content (VWC) over a crop-growing period was performed using the near-infrared (NIR) and short-wave infrared (SWIR) bands of the Terra-MODerate Resolution Imaging Spectroradiometer (Terra-MODIS). The study was conducted in Iowa, USA as part of the Soil Moisture Experiments 2002 (SMEX02). Due to the moderate resolution of MODIS data, the removal of mixed pixels was important in order to meet accuracy estimation requirements of potential applications. MODIS-derived reflectance for the NIR and SWIR bands over corn and soybeans fields was validated using atmospherically corrected Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM) data. All possible combinations of the 7 MODIS bands were used to construct VIs. The performance of each combination was evaluated by computing their correlations with corn VWC. The Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI) were found to be the best candidates. In this study, it was observed that the MODIS SWIR-based VI for corn saturated at a later date than NDVI. A similar late saturation was observed for soybeans with a lag of about 10 days. Linear relationships between the SWIR-based VI and VWC were developed using the MODIS data and ground measured VWC. MODIS-derived Normalized Difference Water Indices (NDWI) using SWIR (1640 nm) or SWIR (2130 nm), namely NDWI1640 or NDWI2130, all showed potential in estimating VWC. Additional testing of this approach could result in a robust technique for estimating VWC for specific crops.
  • Keywords
    MODIS , NDVI , NDWI , Landsat , SMEX02 , Vegetation water content
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2005
  • Journal title
    Remote Sensing of Environment
  • Record number

    1574726