Leaf and canopy water content estimation in cotton using hyperspectral indices and radiative transfer models

Qian, Yi; Wang, Fumin; Bao, Anming; Jiapaer, Guli

doi:10.1016/j.jag.2014.04.019

Cited by 50 publications

(41 citation statements)

References 49 publications

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“…For whole canopies of plants under field conditions, near-infrared (NIR, 700-1100 nm) spectral indices are useful water stress indicators [80,81]. Thus, field-measured hyperspectral remote sensing data is being successfully used to estimate leaf water content and leaf water potential in vineyards [82][83][84][85], cotton fields [86] and maize [87], among other crops.…”

Section: Nir Spectroscopymentioning

confidence: 99%

Plant-Based Methods for Irrigation Scheduling of Woody Crops

Fernández

2017

Horticulturae

131

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Abstract:The increasing world population and expected climate scenarios impel the agricultural sector towards a more efficient use of water. The scientific community is responding to that challenge by developing a variety of methods and technologies to increase crop water productivity. Precision irrigation is intended to achieve that purpose, through the wise choice of the irrigation system, the irrigation strategy, the method to schedule irrigation, and the production target. In this review, the relevance of precision irrigation for a rational use of water in agriculture, and methods related to the use of plant-based measurements for both the assessment of plant water stress and irrigation scheduling, are considered. These include non-automated, conventional methods based on manual records of plant water status and gas exchange, and automated methods where the related variable is recorded continuously and automatically. Thus, the use of methodologies based on the Scholander chamber and portable gas analysers, as well as those of systems for measuring sap flow, stem diameter variation and leaf turgor pressure, are reviewed. Other methods less used but with a potential to improve irrigation are also considered. These include those based on measurements related to the stem and leaf water content, and to changes in electrical potential within the plant. The use of measurements related to canopy temperature, both for direct assessment of water stress and for defining zones with different irrigation requirements, is also addressed. Finally, the importance of choosing the production target wisely, and the need for economic analyses to obtain maximum benefit of the technology related to precision irrigation, are outlined.

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Section: Nir Spectroscopymentioning

confidence: 99%

Plant-Based Methods for Irrigation Scheduling of Woody Crops

Fernández

2017

Horticulturae

131

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“…Knowledge related to vegetation water conditions and how it varies can contribute to accurately detecting the physiological status of vegetation [1][2][3]. It can also provide useful information for making sound decisions related to agriculture irrigation and assist with drought monitoring assessment [2,4,5]. Generally, canopy water content (CWC) and the mean leaf equivalent water thickness at the canopy level ( ̅̅̅̅̅̅̅ ) are widely used for describing the vegetation water status [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…Remote sensing techniques provide a non-destructive, effective, and reliable method for assessing canopy biophysical variables [5]. Hyperspectral remote sensing has been widely used especially to estimate leaf area index (LAI) [14][15][16], fraction of absorbed photosynthetically active radiation (fAPAR) [17,18], chlorophyll content [19][20][21][22], photosynthetic parameters [23], biomass [14], and gross primary production [21,22].…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, studies of vegetation water content using remote sensing techniques have received widespread attention, and have become a focus point during vegetation monitoring and parameter inversion. Currently, a few studies have been conducted on the estimation of vegetation water content using hyperspectral data [5][6][7]10,24,25]. In these studies, two major approaches, physically-based radiative transfer models [5,6,10,24,25] and statistical models mainly including the first derivative reflectance spectra [6,7,25], spectral reflectance indices [5,7,10,24,26], continuum removed spectra analysis [6,10], and full spectrum methods [26] were used.…”

Section: Introductionmentioning

confidence: 99%

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

Zhang

Zhou

2015

Remote Sensing

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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 ( ̅̅̅̅̅̅̅ ) 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 ̅̅̅̅̅̅̅ . Simulated drought in two differently managed irrigation years did not affect the sensitivities of VIs to the variations in CWC and ̅̅̅̅̅̅̅ . However, the relationships between CWC and VIs were more noticeable in 2014 than in 2013. In contrast, ̅̅̅̅̅̅̅ 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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“…Por su parte, CWC es un indicador del estrés hídrico de la cubierta vegetal a nivel de dosel y se ha utilizado en diversas aplicaciones ambientales relacionadas con estudios ecofisiológicos (Ustin et al, 2004), agricultura de precisión (Yi et al, 2014), estudios de variabilidad intra-diaria de la cubierta vegetal (Cheng et al, 2013;Cheng et al, 2014) y estudios forestales de diversa índole (Gao, 1996;Ustin et al, 1998). Este parámetro biofísico se define como el peso del agua por unidad de área de hoja y por unidad de superficie de suelo muestreada (A plot ).…”

Section: Introductionunclassified

Estimación de variables biofísicas del pastizal en un ecosistema de dehesa a partir de espectro-radiometría de campo e imágenes hiperespectrales aeroportadas

et al. 2017

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The aim of this paper is the estimation of biophysical vegetation parameters from its optical properties. The variables Fuel Moisture Content (FMC), Canopy Water Content (CWC), Leaf Area Index (LAI), dry matter (Cm) and AboveGround Biomass (AGB) were estimated in the laboratory from vegetation samples collected simultaneously with the acquisition of spectral data from the Compact Airborne Spectrographic Imager (CASI) sensor and the field spectroradiometer ASD FieldSpec® 3. Spectral vegetation indices found in the literature were computed from hyperspectral data. Their linear relationships with the biophysical variables measured in the field were analysed. Results show consistent relationships between analysed biophysical parameters and spectral indices, mainly those using SWIR and red-egde bands which reveal the importance of these spectral regions for the estimation of biophysical variables in herbaceous covers. Determination coefficients (R2) above 0.91 and RRMSE of 21.4% have been obtained for the spectral indexes calculated whit ASD data, and 0.91 R2 and RRMSE of 15.5% for the spectral indexes calculated whit CASI data.

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Leaf and canopy water content estimation in cotton using hyperspectral indices and radiative transfer models

Cited by 50 publications

References 49 publications

Plant-Based Methods for Irrigation Scheduling of Woody Crops

Plant-Based Methods for Irrigation Scheduling of Woody Crops

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

Estimación de variables biofísicas del pastizal en un ecosistema de dehesa a partir de espectro-radiometría de campo e imágenes hiperespectrales aeroportadas

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