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Light use efficiency (LUE) plays an important role in gross primary production (GPP), so accurate estimation of LUE is crucial. The estimation of LUE using the photochemical reflectance index (PRI) is considerably promising, but on the other hand there is always uncertainty in obtaining the PRI due to the changing viewing angle and sun position in remote sensing observations. The objective of this study was to distinguish between sunlit and shaded leaves to improve the performance of PRI estimating LUE, and we used rice canopy reflectance data collected by the automatic multi-angle remote sensing platform and flux data for each half hour from 9:00 to 15:00 in Shouxian, Anhui Province, China. We modified the two-leaf model based on the characteristics of the rice canopy,was thought of by distinguishing between sunlit and shaded leaves PRI by two-leaf model on the rice canopy. The results showed that the-LUE correlation improved relative to PRI-LUE on clear days and was essentially negligible on cloudy days. We found that the photosynthetically active radiation (PAR), temperature, and humidity had some influence on, the-LUE correlation was strongest at higher temperature and vapour pressure deficit (VPD) and was linear with the change of temperature. We conclude that the modified two-leaf model improves the integrity of the PRI remote sensing observation and increases the accuracy of its LUE estimation by adequately separating sunlit and shaded leaves in the rice canopy.

Improving the ability of PRI in light use efficiency estimation by distinguishing sunlit and shaded leaves in rice canopy