Author/Authors :
Zhao، S. نويسنده State Environmental Protection Key Laboratory of Satellite Remote Sensing,Beijing,China , , Wang، Q. نويسنده Satellite Environmental Center,Ministry of Environmental Protection,Beijing,China , , Yao، Y. نويسنده School of Geography,Beijing Normal University,Beijing,China , , Du، S. نويسنده Institute of Remote Sensing and Geographic Information System,Peking University,Beijing,China , , Zhang، C. نويسنده College of Information Science and Engineering,Shandong Agricultural University,Taian,China , , Li، J. نويسنده Ningxia Provincial Institute of Meteorology,Yinchuan,China , , Zhao، J. نويسنده Xuchang Environmental Monitoring Center,Xuchang,China ,
Abstract :
Water content plays an important role in the process of plant photosynthesis and biomass accumulation. Many methods have been developed to retrieve canopy leaf water content from remote sensing data. However, the validity of these methods has not been verified, which limits their applications. This study estimates the Leaf Water Content (LWC) of winter wheat with three most widely used indexes: Normalized Difference Water Index (NDWI), Simple Ratio (SR), and Shortwave Infrared Perpendicular Water Stress Index (SPSI), as well as MODIS short wave and near infrared data, and then compares remote sensing estimates of vegetation water content with fieldmeasured values measured in concurrent dates. The results indicate that the three indexes are significantly correlated with the LWC of winter wheat at the 0.01 significance level. They all have good accuracy with higher than 90%. The indexes derived from MODIS bands 6 and 2 were better than those from bands 7 and 2 for measuring wheat leaf water content, and the correlations of the former two (NDWI and SR) were stronger than that of SPSI.
Keywords :
Near infrared band , Remote sensing , Short wave infrared band. Spectral characteristic index , Validation
