Spectral indices for tracing leaf water status with hyperspectral reflectance data
Affiliation
School of Geography Development and Environment, The University of ArizonaIssue Date
2023-03-31Keywords
equivalent water thicknessgravimetric water content
hyperspectral indices
plant water concentration
reflectance
remote sensing
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Qazi Muhammad Yasir, Zhijie Zhang, Jiakui Tang, Muhammad Naveed, and Zahid Jahangir "Spectral indices for tracing leaf water status with hyperspectral reflectance data," Journal of Applied Remote Sensing 17(1), 014523 (31 March 2023). https://doi.org/10.1117/1.JRS.17.014523Rights
© The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Plant water stress can be detected via remote sensing. The objective of the study was to determine which leaf water index is best for assessing leaf water content from the laboratory standpoint. This study investigated the relationship between equivalent water thicknesses (EWT), gravimetric water content (GWC), and plant water concentration in the 350-to 2500-nm reflectance spectral range. A total of 277 leaf samples taken from ten different plants were used as calibration dataset, and 605 leaves from different plants, including LOPEX93 and ANGERS database, were used for validation. Three specific indices were analyzed: simple ratio, normalized ratio, and double difference (Datt type of index). A regression approach based on the iteration method at 5-nm interval was used for model calibration. Three bands index was found the most suitable and was validated by 605 leaf samples: for the linear regression model, the index is (R1910-R1340) / (R1910-R1125) with R2 = 0.96 and root mean square error (RMSE) = 0.001 (g / cm2) and, for nonlinear regression model the index is (R1930-R1425) / (R1930-R1360) with R2 = 0.95 and RMSE = 0.001 (g/cm2) for EWT. The newly proposed indices take advantage of being able to eliminate additional noise created by the leaf surface, making them helpful for agricultural-related research. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.Note
Open access articleISSN
1931-3195Version
Final Published Versionae974a485f413a2113503eed53cd6c53
10.1117/1.JRS.17.014523
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Except where otherwise noted, this item's license is described as © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License.