• Title of article

    Application of a simple algorithm to estimate daily evapotranspiration from NOAA–AVHRR images for the Iberian Peninsula

  • Author/Authors

    Sobrino، نويسنده , , J.A. and Gَmez، نويسنده , , M. and Jiménez-Muٌoz، نويسنده , , J.C. and Olioso، نويسنده , , A.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2007
  • Pages
    10
  • From page
    139
  • To page
    148
  • Abstract
    Evapotranspiration (ET) is a key process in land surface–atmosphere studies. It mainly depends on water availability and incoming solar radiation and then reflects the interactions between surface water processes and climate. In this paper, a methodology for retrieving ET from low spatial resolution remote sensing data is presented. It is based on the evaporative fraction concept, and it has been applied to Advanced Very High Resolution Radiometer (AHVRR) data acquired over the Iberian Peninsula. The methodology does not require other data than the data provided by the satellite and may be applied to areas with almost spatially constant atmospheric conditions and which include wet and dry sub-areas. The comparison with high resolution ET estimation shows a root mean square error (RMSE) of 1.4 mm d− 1 which is in agreement with the sensitivity analysis of the method. Finally, the methodology has been applied to temporal NOAA–AVHRR images acquired from 1997 to 2002 in order to analyze the seasonal evolution of the daily ET. The temporal study of the ET values realized in this paper shows that the highest ET values are associated with the higher development crops, while the lowest values are related with lower development or null crop. As a conclusion, it is shown that the ET values obtained with the proposed model evolve according to the variations presented in parameters such as surface temperature or vegetation index.
  • Keywords
    Evaporative fraction , Soil heat flux , Net radiation flux , Latent heat flux , NOAA–AVHRR , Dais , Evapotranspiration , S-SEBI
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2007
  • Journal title
    Remote Sensing of Environment
  • Record number

    1575188