• Title of article

    Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans

  • Author/Authors

    Jackson، نويسنده , , Thomas J. and Chen، نويسنده , , Daoyi and Cosh، نويسنده , , Michael and Li، نويسنده , , Fuqin and Anderson، نويسنده , , Martha and Walthall، نويسنده , , Charles and Doriaswamy، نويسنده , , Paul and Hunt، نويسنده , , E.Ray، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2004
  • Pages
    8
  • From page
    475
  • To page
    482
  • Abstract
    Information about vegetation water content (VWC) has widespread utility in agriculture, forestry, and hydrology. It is also useful in retrieving soil moisture from microwave remote sensing observations. Providing a VWC estimate allows us to control a degree of freedom in the soil moisture retrieval process. However, these must be available in a timely fashion in order to be of value to routine applications, especially soil moisture retrieval. As part of the Soil Moisture Experiments 2002 (SMEX02), the potential of using satellite spectral reflectance measurements to map and monitor VWC for corn and soybean canopies was evaluated. Landsat Thematic Mapper and Enhanced Thematic Mapper Plus data and ground-based VWC measurements were used to establish relationships based on remotely sensed indices. The two indices studied were the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI). The NDVI saturated during the study period while the NDWI continued to reflect changes in VWC. NDWI was found to be superior based upon a quantitative analysis of bias and standard error. The method developed was used to map daily VWC for the watershed over the 1-month experiment period. It was also extended to a larger regional domain. In order to develop more robust and operational methods, we need to look at how we can utilize the MODIS instruments on the Terra and Aqua platforms, which can provide daily temporal coverage.
  • Keywords
    NDWI , Landsat , Vegetation water content
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2004
  • Journal title
    Remote Sensing of Environment
  • Record number

    1574496