• DocumentCode
    743015
  • Title

    Evaluation of Chlorophyll-Related Vegetation Indices Using Simulated Sentinel-2 Data for Estimation of Crop Fraction of Absorbed Photosynthetically Active Radiation

  • Author

    Dong, Taifeng ; Meng, Jihua ; Shang, Jiali ; Liu, Jiangui ; Wu, Bingfang

  • Author_Institution
    Division for Digital Agriculture, Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China
  • Volume
    8
  • Issue
    8
  • fYear
    2015
  • Firstpage
    4049
  • Lastpage
    4059
  • Abstract
    In recent years, the impact of chlorophyll content on the estimation of the fraction of absorbed photosynthetically active radiation (FPAR) has attracted increased attention. In this study, chlorophyll-related vegetation indices (VIs) were selected and tested for their capability in crop FPAR estimation using simulated Sentinel-2 data. These indices can be categorized into four classes: 1) the ratio indices; 2) the normalized difference indices; 3) the triangular area-based indices; and 4) the integrated indices. Two crops, wheat and corn, with distinctive canopy and leaf structure were studied. Measured FPAR and Sentinel-2 reflectance simulated from field spectral measurements were used. The results showed that VIs using the near-infrared and red-edge reflectance, including the modified Simple Ratio-2 (mSR2), the red-edge Simple Ratio ( text{SR}_{705} ), the Red-Edge Normalized Difference Vegetation Index ( text{ND}_{705} ), MERIS Terrestrial Chlorophyll Index (MTCI), and the Revised Optimized Soil-Adjusted Vegetation Index (OSAVI[705, 750]), had a strong linear correlation with FPAR, especially in the high biomass range. When the red-edge reflectance was used, the ratio indices (e.g., mSR2 and text{SR}_{705} ) had a stronger correlation with crop FPAR than the normalized difference indices (e.g., text{ND}_{705} ). Sensitivity analysis showed that mSR2 had the strongest linear correlation with FPAR of the two crops across a growing season. Further analysis indicated that indices using the red-edge reflectance might be useful for developing FPAR retrieval algorithms that are independent of crop types. This suggests the potential for high resolution - nd high-quality mapping of FPAR for precision farming using the Sentinel-2 data.
  • Keywords
    Agriculture; Correlation; Estimation; Indexes; Remote sensing; Soil measurements; Vegetation mapping; Chlorophyll-related vegetation indices; Sentinel-2; crop FPAR; red-edge reflectance;
  • fLanguage
    English
  • Journal_Title
    Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    1939-1404
  • Type

    jour

  • DOI
    10.1109/JSTARS.2015.2400134
  • Filename
    7050317