Remote Sensing Applications and Decision Support

Estimation of carotenoid content at the canopy scale using the carotenoid triangle ratio index from in situ and simulated hyperspectral data

[+] Author Affiliations
Weiping Kong, Xianfeng Zhou

Institute of Remote Sensing and Digital Earth, Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094, China

University of Chinese Academy of Sciences, 19A Yuquan Road, Shijingshan District, Beijing 100049, China

Wenjiang Huang

Institute of Remote Sensing and Digital Earth, Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094, China

Xiaoyu Song

Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, No. 11 Shuguang Hua Yuan Middle Road, Haidian District, Beijing 100097, China

Raffaele Casa

Università degli Studi della Tuscia, Department of Agricultural and Forestry Sciences, Via San Camillo de Lellis, 01100 Viterbo, Italy

J. Appl. Remote Sens. 10(2), 026035 (Jun 17, 2016). doi:10.1117/1.JRS.10.026035
History: Received January 28, 2016; Accepted May 13, 2016
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Abstract.  Precise estimation of carotenoids (Car) content in plants, from remotely sensed data, is challenging due to their small proportion in the overall total pigment content and to the overlapping of spectral absorption features with chlorophyll (Chl) in the blue region of the spectrum. The use of narrow band vegetation indices (VIs) obtained from hyperspectral data has been considered an effective way to estimate Car content. However, VIs have proved to lack sensitivity to low or high Car content in a number of studies. In this study, the carotenoid triangle ratio index (CTRI), derived from the existing modified triangular vegetation index and a single band reflectance at 531 nm, was proposed and employed to estimate Car canopy content. We tested the potential of three categories of hyperspectral indices earlier proposed for Car, Chl, Car/Chl ratio estimation, and the new CTRI index, for Car canopy content assessment in winter wheat and corn. Spectral reflectance representing plant canopies were simulated using the PROSPECT and SAIL radiative transfer model, with the aim of analyzing saturation effects of these indices, as well as Chl effects on the relationship between spectral indices and Car content. The result showed that the majority of the spectral indices tested, saturated with the increase of Car canopy content above 28 to 64  μg/cm2. Conversely, the CTRI index was more robust and was linearly and highly sensitive to Car content in winter wheat and corn datasets, with coefficients of determination of 0.92 and 0.75, respectively. The corresponding root mean square error of prediction were 6.01 and 9.70  μg/cm2, respectively. Furthermore, the CTRI index did not show a saturation effect and was not greatly influenced by changes of Chl values, outperforming all the other indices tested. Estimation of Car canopy content using the CTRI index provides an insight into diagnosing plant physiological status and environmental stress.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Weiping Kong ; Wenjiang Huang ; Xianfeng Zhou ; Xiaoyu Song and Raffaele Casa
"Estimation of carotenoid content at the canopy scale using the carotenoid triangle ratio index from in situ and simulated hyperspectral data", J. Appl. Remote Sens. 10(2), 026035 (Jun 17, 2016). ; http://dx.doi.org/10.1117/1.JRS.10.026035


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