Assessment of in situ crop LAI measurement using unidirectional view digital photography.
Liu, J., Pattey, E., and Admiral, S. (2013). "Assessment of in situ crop LAI measurement using unidirectional view digital photography.", Agricultural and Forest Meteorology, 169, pp. 25-34. doi : 10.1016/j.agrformet.2012.10.009 Access to full text
This study evaluated the performance of digital photography for measuring the green leaf area index (LAI) and green plant area index (GAI) of field crops by quantifying gap fraction either at nadir or at a 57.5° view angle. Clumping index was estimated using the logarithmic averaging method of Lang and Xiang (1986) to derive the total GAI. Measurement uncertainty associated with foliage inclination and view angles was assessed analytically, as was image classification. The GAI derived for corn, soybean and wheat crops was strongly linearly correlated with the destructive GAI for both the nadir and the 57.5° photographic methods (R2 > 0.83, root mean square error < 0.63). Because the destructive LAI and GAI exhibited strong linear correlations for soybean and corn, LAI could be predicted from photographic methods. The LAI and GAI of the wheat canopy were poorly correlated because of a significant proportion of non-leaf tissues contributing to photosynthesis after the start of stem elongation. Clumping had a greater effect on the nadir photographic method than on the 57.5° method. The effective GAI from nadir viewing was better correlated to the destructive GAI than the photographic GAI, whereas the effective GAI from the 57.5° photographic method provided a greater underestimation of the destructive GAI than the photographic GAI. The extinction coefficient at nadir viewing was found to be 22% larger than the assumed value (i.e. k = 0.61 vs. the theoretical value of 0.5). When gap reduction reached the asymptotic saturation level with increasing LAI, higher classification accuracy was required to achieve acceptable LAI measurement accuracy. The 57.5° photographic method was more affected by classification accuracy when LAI was higher than 1.5. With crop canopy development, the decrease in gap size and the decline in signal strength from shadows mean that high-quality photos are required to effectively differentiate gaps from plant tissues.
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