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Remote Sens. 2015, 7(11), 15203-15223; doi:10.3390/rs71115203

Estimation of Canopy Water Content by Means of Hyperspectral Indices Based on Drought Stress Gradient Experiments of Maize in the North Plain China

1
State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
2
Chinese Academy of Meteorological Sciences, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Academic Editors: Pablo J. Zarco-Tejada, Clement Atzberger and Prasad S. Thenkabail
Received: 17 August 2015 / Revised: 1 November 2015 / Accepted: 3 November 2015 / Published: 12 November 2015
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Abstract

Here, we conducted drought stress gradient experiments of maize, and used ten water content related vegetation indices (VIs) to estimate widely variable canopy water content (CWC) and mean leaf equivalent water thickness at canopy level (\({\overline{EWT}}\)) based on in situ measurements of Lambertian equivalent reflectance and important biological and environmental factors during the 2013−2014 growing seasons in the North China Plain. Among ten VIs, the performances of green chlorophyll index (CIgreen), red edge chlorophyll index (CIred edge), and the red edge normalized ratio (NRred edge) were most sensitive to the variations of CWC and \({\overline{EWT}}\). Simulated drought in two differently managed irrigation years did not affect the sensitivities of VIs to the variations in CWC and \({\overline{EWT}}\). However, the relationships between CWC and VIs were more noticeable in 2014 than in 2013. In contrast, \({\overline{EWT}}\) and VIs were more closely related in 2013 than in 2014. CWC and relative soil water content (RSWC) obviously exhibited a two-dimensional trapezoid space, which illustrated that CWC was determined not only by soil water status but also by crop growth and stage of development. This study demonstrated that nearly half of the variation in CWC explained by spectral information was derived from the variation in leaf area index (LAI). View Full-Text
Keywords: canopy water content; drought stress gradients; hyperspectral remote sensing; maize canopy; spectral vegetation indices canopy water content; drought stress gradients; hyperspectral remote sensing; maize canopy; spectral vegetation indices
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhang, F.; Zhou, G. Estimation of Canopy Water Content by Means of Hyperspectral Indices Based on Drought Stress Gradient Experiments of Maize in the North Plain China. Remote Sens. 2015, 7, 15203-15223.

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