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Title: Evaluation of average leaf inclination angle quantified by indirect optical instruments in crop fields

Journal Article · · International Journal of Applied Earth Observation and Geoinformation

Average leaf inclination angle ($$\overline{θ}$$L) is an important canopy structure variable that influences light regime, photosynthesis, and evapotranspiration of plants. $$\overline{θ}$$L can be measured through direct methods (e.g., protractor), which are labor-intensive and time-consuming, or through indirect optical instruments, which are more efficient than the direct methods. However, uncertainties of different indirect optical instruments for quantifying $$\overline{θ}$$L remain largely unquantified. In this study, we evaluated and compared the performances of three major indirect optical instruments: (1) LAI-2200, (2) 30°-tilted camera, and (3) digital hemispherical photography (DHP), in different crop fields over a growing season, benchmarked with direct measurements. LAI-2200 and 30°-tilted camera showed higher agreement with direct $$\overline{θ}$$ measurements (R2 = 0.54, RMSE = 7.37°; R2 = 0.58, RMSE = 8.08°) than DHP (R2 = 0.14, RMSE = 13.96°). Different performances of indirect optical instruments could be attributed to the accuracy of gap fraction measurement and the performance of the $$\overline{θ}$$L quantification algorithms. When using the LAI-2200 algorithm, larger gap fraction gradients over view zenith angles led to larger $$\overline{θ}$$L values, and smaller gap fraction gradients led to smaller $$\overline{θ}$$L values. Such error propagation was larger in sparse canopy than in dense canopy. The Wilson G function of the LAI-2200 algorithm performed better in estimating $$\overline{θ}$$L than the G function based on the ellipsoidal LAD function used by the CAN_EYE algorithm. We also proposed a modification of the LAI-2200 algorithm, which further improved the performance of LAI-2200 and 30°-tilted cameras in estimating $$\overline{θ}$$L. We envision that the low-cost 30°-tilted cameras provide a promising sensor solution to continuously monitor canopy structure for various ecosystems.

Research Organization:
Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), Urbana, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
SC0018420
OSTI ID:
2473656
Journal Information:
International Journal of Applied Earth Observation and Geoinformation, Journal Name: International Journal of Applied Earth Observation and Geoinformation Vol. 134; ISSN 1569-8432
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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