Chin J Plan Ecolo ›› 2014, Vol. 38 ›› Issue (7): 710-719.doi: 10.3724/SP.J.1258.2014.00066

• Research Articles • Previous Articles     Next Articles

Estimating canopy photosynthetic parameters in maize field based on multi-spectral remote sensing

ZHANG Feng1 and ZHOU Guang-Sheng1,2*   

  1. 1State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China;

    2Chinese Academy of Meteorological Sciences, Beijing 100081, China
  • Received:2013-12-31 Revised:2014-05-07 Online:2014-07-10 Published:2014-07-01
  • Contact: ZHOU Guang-Sheng


Aims Determination of canopy photosynthetic parameters is key to accurate simulation of ecosystem function by using remote sensing methods. Currently, remote estimation of vegetation canopy structure characteristics has been widely adopted. However, directly estimating photosynthetic variables (photosynthetic capacity and efficiency) at canopy scale based on field spectrometry combined with CO2 flux measurements is rare.
Methods In this study, we remotely estimated solar radiation use efficiency (εN, net ecosystem CO2 exchange/absorbed photosynthetically active radiation (NEECO2/APAR); εG, gross primary productivity/absorbed photosynthetically active radiation (GPP/APAR); α, apparent quantum efficiency) and photosynthetic capacity (Pmax) based on in situ measurements of spectral reflectance and ecosystem CO2 fluxes, along with observational data on micrometeorological factors during the entire growing season for a maize canopy in Northeast China.
Important findings Results showed that the seasonal variations in Pmax and α exhibited a single peak; whereas the values of εN and εG were higher at the start of vegetative stage and then rapidly decreased with the development of maize until displaying a single peak at the intermediate and late stages of the growing season, coinciding with the occurrence of peak values in Pmax. A comparison was made on the predictive performance based on normalized difference vegetation index (NDVI), ratio vegetation index (RVI), wide dynamic range vegetation index (WDRVI), 2-band enhanced vegetation index (EVI2), and chlorophyll index (CI) in estimating four canopy photosynthetic parameters with any combination of two separate wavelengths at the range of 400–1 300 nm, which showed that EVI2 was most closely and linearly related to photosynthetic capacity and efficiency. This study demonstrates that multi-spectral remote sensing information is sensitive to the variations in canopy photosynthetic parameters in maize field and can be used to quantitatively monitor seasonal dynamics of canopy photosynthesis, and to accurately assess crop productivity and ecosystem CO2 exchange capacity.

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