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Journal of Applied Remote Sensing

Estimation of carotenoid content at the canopy scale using the carotenoid triangle ratio index from <italic<in situ</italic< and simulated hyperspectral data
Author(s): Weiping Kong; Wenjiang Huang; Xianfeng Zhou; Xiaoyu Song; Raffaele Casa
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Paper 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.

Paper Details

Date Published: 17 June 2016
PDF: 20 pages
J. Appl. Remote Sens. 10(2) 026035 doi: 10.1117/1.JRS.10.026035
Published in: Journal of Applied Remote Sensing Volume 10, Issue 2
Show Author Affiliations
Weiping Kong, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Wenjiang Huang, Institute of Remote Sensing and Digital Earth (China)
Xianfeng Zhou, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Xiaoyu Song, National Engineering Research Ctr. for Information Technology in Agriculture (China)
Raffaele Casa, Univ. degli Studi della Tuscia (Italy)


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