Jin, PB; Wang, Q; Iio, A; Tenhunen, J (2012). Retrieval of seasonal variation in photosynthetic capacity from multi-source vegetation indices. ECOLOGICAL INFORMATICS, 7(1), 7-18.
Seasonal information on photosynthetic-capacity parameters (maximum carboxylation velocity, V-cmax; and maximum rate of electron transport, J(max)) plays an important role in accurate simulation of carbon fixation in gas-exchange models. Exact inclusion of seasonal information on photosynthetic-capacity parameters into the models has been an irresolvable challenge. This paper investigated the relationships between vegetation indices (from multiple sources) and photosynthetic-capacity parameters of three beech forest stands (Fagus crenata) along an elevation gradient in the cold-temperate zone of Japan, over the entire growing season of 2006. Diverse vegetation indices were examined in terms of spectral, spatial and temporal scales; ranging from meteorological sensor-based broadband indices to hyperspectral data-based narrowband indices, to simulated MODIS (MODerate-resolution Imaging Spectroradiometer) indices based on hyperspectral data, and finally satellite-borne MODIS vegetation indices. Regression analysis revealed that all examined indices, with the exception of the downloaded MODIS products, had significant regression relationships with photosynthetic parameters (P<0.001) when all data were pooled. Among the different indices, the simulated MODIS NDVI (Normalized Difference Vegetation Index) performed the best for both V-cmax and J(max) (R-2=0.81 and 0.73, respectively). Site differences were apparent, as the simulated MODIS NDVI performed the best in exponential regressions for the 550 m site, while broadband NDVI performed best in exponential regression models for the 900 m site. The broadband SR (Simple Ratio) in relation to V-cmax performed best with respect to a linear model, whereas the broadband NDVI with J(max) performed the best in an exponential model for the 1500 m site. The results reveal that vegetation indices which are obtained across different scales nevertheless retain tight relationships with canopy-scale photosynthetic-capacity parameters. The established relationships were inversely applicable to derive seasonal trajectories of photosynthetic-capacity parameters. Thus, new insight and confidence is gained for using remotely estimated photosynthetic parameters, even though most previous research works were limited on linking of vegetation indices with biophysical parameters. The control effect of physiological capacity on reflectance and further on vegetation indices has not been adequately established and thus needs further orientation for rigorous research work. (C) 2011 Elsevier B.V. All rights reserved.