TY - JOUR

T1 - A new vegetation index combination for leaf carotenoid-to-chlorophyll ratio

T2 - minimizing the effect of their correlation

AU - He, Chunmei

AU - Sun, Jia

AU - Chen, Yuwen

AU - Wang, Lunche

AU - Shi, Shuo

AU - Qiu, Feng

AU - Wang, Shaoqiang

AU - Tagesson, Torbern

N1 - Publisher Copyright: © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

PY - 2023

Y1 - 2023

N2 - The ratio of leaf carotenoid to chlorophyll (Car/Chl) is an indicator of vegetation photosynthesis, development and responses to stress. However, the correlation between Car and Chl, and their overlapping absorption in the visible spectral domain pose a challenge for optical remote sensing of their ratio. This study aims to investigate combinations of vegetation indices (VIs) to minimize the influence of Car-Chl correlation, thus being more sensitive to the variability in the ratio across vegetation species and sites. VIs sensitive to Car and Chl variability were combined into four candidates of combinations, using a simulated dataset from the PROSPECT model. The VI combinations were then tested using six simulated datasets with different Car-Chl correlations, and evaluated against four independent datasets. The ratio of the carotenoid triangle ratio index (CTRI) with the red-edge chlorophyll index (CIred-edge) was found least influenced by the Car-Chl correlation and demonstrated a superior ability for estimating Car/Chl variability. Compared with published VIs and two machine learning algorithms, CTRI/CIred-edge also showed the optimal performance in the four field datasets. This new VI combination could be useful to provide insights in spatiotemporal variability in the leaf Car/Chl ratio, applicable for assessing vegetation physiology, phenology, and response to environmental stress. Trial registration:Clinical Trials Registry India identifier: CTRI/.

AB - The ratio of leaf carotenoid to chlorophyll (Car/Chl) is an indicator of vegetation photosynthesis, development and responses to stress. However, the correlation between Car and Chl, and their overlapping absorption in the visible spectral domain pose a challenge for optical remote sensing of their ratio. This study aims to investigate combinations of vegetation indices (VIs) to minimize the influence of Car-Chl correlation, thus being more sensitive to the variability in the ratio across vegetation species and sites. VIs sensitive to Car and Chl variability were combined into four candidates of combinations, using a simulated dataset from the PROSPECT model. The VI combinations were then tested using six simulated datasets with different Car-Chl correlations, and evaluated against four independent datasets. The ratio of the carotenoid triangle ratio index (CTRI) with the red-edge chlorophyll index (CIred-edge) was found least influenced by the Car-Chl correlation and demonstrated a superior ability for estimating Car/Chl variability. Compared with published VIs and two machine learning algorithms, CTRI/CIred-edge also showed the optimal performance in the four field datasets. This new VI combination could be useful to provide insights in spatiotemporal variability in the leaf Car/Chl ratio, applicable for assessing vegetation physiology, phenology, and response to environmental stress. Trial registration:Clinical Trials Registry India identifier: CTRI/.

KW - Leaf carotenoids content

KW - leaf chlorophyll content

KW - PROSPECT model

KW - ratio of Car to Chl

KW - vegetation index

U2 - 10.1080/17538947.2023.2168772

DO - 10.1080/17538947.2023.2168772

M3 - Journal article

AN - SCOPUS:85148543337

VL - 16

SP - 272

EP - 288

JO - International Journal of Digital Earth

JF - International Journal of Digital Earth

SN - 1753-8947

IS - 1

ER -