PROGRESS IN GEOGRAPHY ›› 2016, Vol. 35 ›› Issue (1): 25-34.doi: 10.18306/dlkxjz.2016.01.004

• Orginal Article • Previous Articles     Next Articles

Progress on grassland chlorophyll content estimation by hyperspectral analysis

Wenyong MA(), Xunming WANG*()   

  1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Online:2016-01-31 Published:2016-01-31
  • Contact: Xunming WANG;
  • Supported by:
    National Science Fund for Distinguished Young Scholars of China, No.41225001


As the key pigment for photosynthesis, chlorophyll is closely related to nitrogen, protein, moisture, and other biochemical parameters of vegetation. Chlorophyll is a good indicator for photosynthesis activity and physiological state of grasslands. Hyperspectral analysis is a powerful means for accurately retrieving grassland chlorophyll contents in large areas. Based on the existing methods for monitoring grassland chlorophyll contents, this article summarizes and groups such methods into two categories: empirical models of red edge position (REP) / spectral indices, and radiative transfer models. With statistical analysis of the relationships between chlorophyll contents and REP/ spectral indices, empirical models were extensively employed for estimating grassland chlorophyll contents. These models use simple parameters and the REP that is closely related to grassland chlorophyll contents can be conveniently calculated. Due to the diverse structural forms of the spectral indices and the complicated relationships between spectral indices and chlorophyll contents, accuracy of chlorophyll content estimation is still limited, although novel algorithms of REP calculation and, to a lesser extent, new spectral indices, have significantly improved the estimation accuracy of grassland chlorophyll contents. Based on the relationships of chlorophyll contents and radiation energy, radiative transfer models were founded. Multiple parameters are required in the models, which are highly sensitive to the scale of estimation, and these models need to be further improved. Currently there exist few studies on grassland chlorophyll content estimation and only very few models have been developed for grassland chlorophyll content estimation. Future research should focus on developing new indices or improving existing indices and determining appropriate parameters of radiative transfer models to achieve better results for grassland application. In addition, current studies are limited to leaf and canopy scale analyses, and therefore expanding grassland chlorophyll content estimation to the landscape scale will be an important and challenging task.

Key words: hyperspectral analysis, grassland chlorophyll, red edge position, spectral index, radiative transfer model