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

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 Lambert...

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Main Authors: Feng Zhang, Guangsheng Zhou
Format: Article
Language:English
Published: MDPI AG 2015-11-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/7/11/15203
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author Feng Zhang
Guangsheng Zhou
author_facet Feng Zhang
Guangsheng Zhou
author_sort Feng Zhang
collection DOAJ
description 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).
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spelling doaj.art-2fb38faee3524aa6ae67ae80552da6692022-12-21T19:23:21ZengMDPI AGRemote Sensing2072-42922015-11-01711152031522310.3390/rs71115203rs71115203Estimation of Canopy Water Content by Means of Hyperspectral Indices Based on Drought Stress Gradient Experiments of Maize in the North Plain ChinaFeng Zhang0Guangsheng Zhou1State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, ChinaChinese Academy of Meteorological Sciences, Beijing 100081, ChinaHere, 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).http://www.mdpi.com/2072-4292/7/11/15203canopy water contentdrought stress gradientshyperspectral remote sensingmaize canopyspectral vegetation indices
spellingShingle Feng Zhang
Guangsheng Zhou
Estimation of Canopy Water Content by Means of Hyperspectral Indices Based on Drought Stress Gradient Experiments of Maize in the North Plain China
Remote Sensing
canopy water content
drought stress gradients
hyperspectral remote sensing
maize canopy
spectral vegetation indices
title Estimation of Canopy Water Content by Means of Hyperspectral Indices Based on Drought Stress Gradient Experiments of Maize in the North Plain China
title_full Estimation of Canopy Water Content by Means of Hyperspectral Indices Based on Drought Stress Gradient Experiments of Maize in the North Plain China
title_fullStr Estimation of Canopy Water Content by Means of Hyperspectral Indices Based on Drought Stress Gradient Experiments of Maize in the North Plain China
title_full_unstemmed Estimation of Canopy Water Content by Means of Hyperspectral Indices Based on Drought Stress Gradient Experiments of Maize in the North Plain China
title_short Estimation of Canopy Water Content by Means of Hyperspectral Indices Based on Drought Stress Gradient Experiments of Maize in the North Plain China
title_sort estimation of canopy water content by means of hyperspectral indices based on drought stress gradient experiments of maize in the north plain china
topic canopy water content
drought stress gradients
hyperspectral remote sensing
maize canopy
spectral vegetation indices
url http://www.mdpi.com/2072-4292/7/11/15203
work_keys_str_mv AT fengzhang estimationofcanopywatercontentbymeansofhyperspectralindicesbasedondroughtstressgradientexperimentsofmaizeinthenorthplainchina
AT guangshengzhou estimationofcanopywatercontentbymeansofhyperspectralindicesbasedondroughtstressgradientexperimentsofmaizeinthenorthplainchina