2016
DOI: 10.3390/rs8070557
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Remote Sensing of Grass Response to Drought Stress Using Spectroscopic Techniques and Canopy Reflectance Model Inversion

Abstract: Abstract:The aim of this study was to follow the response to drought stress in a Poa pratensis canopy exposed to various levels of soil moisture deficit. We tracked the changes in the canopy reflectance (450-2450 nm) and retrieved vegetation properties (Leaf Area Index (LAI), leaf chlorophyll content (Cab), leaf water content (Cw), leaf dry matter content (Cdm) and senescent material (Cs)) during a drought episode. Spectroscopic techniques and radiative transfer model (RTM) inversion were employed to monitor t… Show more

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Cited by 60 publications
(66 citation statements)
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References 83 publications
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“…This feature is essential for monitoring plant responses to environmental stress; for example, using repeat reflectance spectroscopy measurements, Bayat et al . () monitored phenological changes in pigment content and leaf morphology in grasses subjected to different levels of drought stress.…”
Section: Spectroscopy: Biochemical and Biophysical Fingerprintingmentioning
confidence: 99%
“…This feature is essential for monitoring plant responses to environmental stress; for example, using repeat reflectance spectroscopy measurements, Bayat et al . () monitored phenological changes in pigment content and leaf morphology in grasses subjected to different levels of drought stress.…”
Section: Spectroscopy: Biochemical and Biophysical Fingerprintingmentioning
confidence: 99%
“…Bayat et al [7] used spectroscopic techniques and radiative transfer model (RTM) inversion to monitor the response to drought stress in a Poa pratensis (or meadow grass) canopy exposed to various levels of soil moisture deficit. The canopy reflectance and destructive measurements of LAI (Leaf Area Index) and leaf chlorophyll content (Cab) were taken.…”
Section: Drought Detectionmentioning
confidence: 99%
“…Four statistical parameters, the root mean square error (RMSE), the determination coefficient (R 2 ), the normalized root mean square error (NRMSE) and relative root mean square error (RRMSE) [82] were used to quantify the goodness-of-fit between derived and measured water-leaving reflectance values at the NIOZ jetty data where near-concurrent (±1 h) MERIS measurements were available. To do this, three MERIS bands 3, 5 and 7 were selected.…”
Section: Atmospheric Correctionmentioning
confidence: 99%