2018•International Journal of Remote SensingRequires access
Assessing spectral indices to estimate the fraction of photosynthetically active radiation absorbed by the vegetation canopy
Dailiang Peng, Helin Zhang, Le Yu, Mingquan Wu, Fumin Wang, Wenjiang Huang, Liangyun Liu, Rui Sun, Cunjun Li, Dacheng Wang, Fubao Xu
Open publisher page 29 citations
Abstract
The fraction of absorbed photosynthetically active radiation (FPAR) by the vegetation canopy (FPARcanopy) is an important parameter for vegetation productivity estimation using remote-sensing data. FPARcanopy is widely estimated using many different spectral vegetation indices (VIs), especially the simple ratio vegetation index (SR) and normalized difference vegetation index (NDVI). However, there have been few studies into which VIs are most suitable for this estimation or into their sensitivities to the leaf area index and the observation geometry of remote-sensing data, which are very important for the accurate estimation of FPARcanopy based on the plant growth stage and satellite imagery. In this study, nine main VIs calculated from field-measured spectra were evaluated and it was found that the SR and NDVI underestimated and overestimated FPARcanopy, respectively. It was also found that the enhanced vegetation index produced lesser errors and a higher agreement than other broadband VIs used to estimate FPARcanopy. Among all the selected VIs, the photochemical reflectance index (PRI) turned out to have the lowest root mean square error of 0.17. The SR produced the highest errors (about 0.37) and lowest index of agreement (about 0.50) compared to the measured values of FPARcanopy. Except for carotenoid reflectance index (CRI), FPARcanopy estimated by VIs are evidently sensitive to the leaf area index (LAI), especially for FPARcanopy (SR), which are also most sensitive to solar zenith angles (SZA). SR, CRI, PRI, and EVI have remarked variations with view zenith angles. Our study shows that FPARcanopy can be simply and accurately estimated using the most suitable VIs – i.e. EVI and PRI – with broadband and hyperspectral remote-sensing data, respectively, and that the nadir reflectance or nadir bidirectional reflectance distribution function adjusted reflectance should be used to calculate these VIs.