Assessment of red-edge vegetation indices for crop leaf area index estimation

被引:218
作者
Dong, Taifeng [1 ]
Liu, Jiangui [1 ]
Shang, Jiali [1 ]
Qian, Budong [1 ]
Ma, Baoluo [1 ]
Kovacs, John M. [2 ]
Walters, Dan [2 ]
Jiao, Xianfeng [1 ]
Geng, Xiaoyuan [1 ]
Shi, Yichao [1 ,3 ]
机构
[1] Agr & Agrifood Canada, Sceince & Technol Branch, Ottawa, ON K1A 0C6, Canada
[2] Nipissing Univ, Geog Dept, North Bay, ON P1B 8L7, Canada
[3] Iowa State Univ, Ames, IA 50011 USA
关键词
Leaf area index; Vegetation index; RapidEye; red-edge; Sensitivity analysis; Crops; VEN-MU-S; GREEN LAI; SPECTRAL REFLECTANCE; CHLOROPHYLL CONTENT; DATA ASSIMILATION; REMOTE ESTIMATION; FRACTION; MODEL; ALGORITHMS; RETRIEVAL;
D O I
10.1016/j.rse.2018.12.032
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study explores the potential of vegetation indices (VIs) for crop leaf area index (LAI) estimation, with a focus on comparing red-edge reflectance based (RE-based) and the visible reflectance based (VIS-based) VIs. Seven VIs were derived from multi-temporal RapidEye images to correlate with LAI of two crop species having contrasting leaf structures and canopy architectures: spring wheat (a monocot) and canola (a dicot) in northern Ontario, Canada. The relationship between LAI and the selected VIs (LAI-VI) was characterized using a semi empirical model. The Markov Chain Monte Carlo (MCMC) sampling method was used to estimate the model parameters, including the extinction coefficient (K-VI) and VI value for dense green canopy (VI infinity). Results showed that crop-specific regression models were much closer to a generic regression model using the RE-based VIs than using the VIS-based VIs. Furthermore, the joint posterior probability distribution of the K-VI and VI infinity of the RE-based VIs tended to converge for the two crops. This suggests that the RE-based VIs are not as sensitive to canopy structure, e.g., the average leaf angle (ALA), as the VIS-based VIs. This is also demonstrated by the sensitivity analyses using both PROSAIL simulations and field measurements. Hence, the RE-based VIs can be used to develop a more generic LAI estimation algorithm for different crops. Further studies are required to assess the impact of soil reflectance and other factors, such as illumination-target-viewing geometries and atmospheric conditions, on LAI retrieval.
引用
收藏
页码:133 / 143
页数:11
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