scholarly journals Hyperspectral Inversion Model of Chlorophyll Content in Peanut Leaves

2020 ◽  
Vol 10 (7) ◽  
pp. 2259 ◽  
Author(s):  
Haixia Qi ◽  
Bingyu Zhu ◽  
Lingxi Kong ◽  
Weiguang Yang ◽  
Jun Zou ◽  
...  
Keyword(s):  
Chlorophyll Content ◽  
Spectral Index ◽  
Spectral Reflectance ◽  
Near Infrared ◽  
Plant Density ◽  
Cell Structure ◽  
Spectral Bands ◽  
Study Results ◽  
Leaf Spectral Reflectance ◽  
Estimation Models

The purpose of this study is to determine a method for quickly and accurately estimating the chlorophyll content of peanut plants at different plant densities. This was explored using leaf spectral reflectance to monitor peanut chlorophyll content to detect sensitive spectral bands and the optimum spectral indicators to establish a quantitative model. Peanut plants under different plant density conditions were monitored during three consecutive growth periods; single-photon avalanche diode (SPAD) and hyperspectral data derived from the leaves under the different plant density conditions were recorded. By combining arbitrary bands, indices were constructed across the full spectral range (350–2500 nm) based on blade spectra: the normalized difference spectral index (NDSI), ratio spectral index (RSI), difference spectral index (DSI) and soil-adjusted spectral index (SASI). This enabled the best vegetation index reflecting peanut-leaf SPAD values to be screened out by quantifying correlations with chlorophyll content, and the peanut leaf SPAD estimation models established by regression analysis to be compared and analyzed. The results showed that the chlorophyll content of peanut leaves decreased when plant density was either too high or too low, and that it reached its maximum at the appropriate plant density. In addition, differences in the spectral reflectance of peanut leaves under different chlorophyll content levels were highly obvious. Without considering the influence of cell structure as chlorophyll content increased, leaf spectral reflectance in the visible (350–700 nm): near-infrared (700–1300 nm) ranges also increased. The spectral bands sensitive to chlorophyll content were mainly observed in the visible and near-infrared ranges. The study results showed that the best spectral indicators for determining peanut chlorophyll content were NDSI (R520, R528), RSI (R748, R561), DSI (R758, R602) and SASI (R753, R624). Testing of these regression models showed that coefficient of determination values based on the NDSI, RSI, DSI and SASI estimation models were all greater than 0.65, while root mean square error values were all lower than 2.04. Therefore, the regression model established according to the above spectral indicators was a valid predictor of the chlorophyll content of peanut leaves.

scholarly journals The Value of Sentinel-2 Spectral Bands for the Assessment of Winter Wheat Growth and Development

2019 ◽  
Vol 11 (17) ◽  
pp. 2050 ◽  
Author(s):  
Andrew Revill ◽  
Anna Florence ◽  
Alasdair MacArthur ◽  
Stephen Hoad ◽  
Robert Rees ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Chlorophyll Content ◽  
Management Practices ◽  
Near Infrared ◽  
Spectral Characteristics ◽  
Crop Management ◽  
Area Index ◽  
Spectral Bands ◽  
The Mean ◽  
Sentinel 2

Leaf Area Index (LAI) and chlorophyll content are strongly related to plant development and productivity. Spatial and temporal estimates of these variables are essential for efficient and precise crop management. The availability of open-access data from the European Space Agency’s (ESA) Sentinel-2 satellite—delivering global coverage with an average 5-day revisit frequency at a spatial resolution of up to 10 metres—could provide estimates of these variables at unprecedented (i.e., sub-field) resolution. Using synthetic data, past research has demonstrated the potential of Sentinel-2 for estimating crop variables. Nonetheless, research involving a robust analysis of the Sentinel-2 bands for supporting agricultural applications is limited. We evaluated the potential of Sentinel-2 data for retrieving winter wheat LAI, leaf chlorophyll content (LCC) and canopy chlorophyll content (CCC). In coordination with destructive and non-destructive ground measurements, we acquired multispectral data from an Unmanned Aerial Vehicle (UAV)-mounted sensor measuring key Sentinel-2 spectral bands (443 to 865 nm). We applied Gaussian processes regression (GPR) machine learning to determine the most informative Sentinel-2 bands for retrieving each of the variables. We further evaluated the GPR model performance when propagating observation uncertainty. When applying the best-performing GPR models without propagating uncertainty, the retrievals had a high agreement with ground measurements—the mean R2 and normalised root-mean-square error (NRMSE) were 0.89 and 8.8%, respectively. When propagating uncertainty, the mean R2 and NRMSE were 0.82 and 11.9%, respectively. When accounting for measurement uncertainty in the estimation of LAI and CCC, the number of most informative Sentinel-2 bands was reduced from four to only two—the red-edge (705 nm) and near-infrared (865 nm) bands. This research demonstrates the value of the Sentinel-2 spectral characteristics for retrieving critical variables that can support more sustainable crop management practices.

scholarly journals USING LEGACY SOIL DATA FOR STANDARDIZING PREDICTIONS OF TOPSOIL CLAY CONTENT OBTAINED FROM VNIR/SWIR HYPERSPECTRAL AIRBORNE IMAGES

2015 ◽  
Vol XL-3/W3 ◽  
pp. 439-444
Author(s):  
C. Gomez ◽  
A. Gholizadeh ◽  
L. Borůvka ◽  
P. Lagacherie
Keyword(s):  
Soil Properties ◽  
Spectral Index ◽  
Near Infrared ◽  
Soil Property ◽  
Clay Content ◽  
Short Wave ◽  
Soil Samples ◽  
Spectral Bands ◽  
Large Sets ◽  
The One

Mapping of topsoil properties using Visible, Near-Infrared and Short Wave Infrared (VNIR/SWIR) hyperspectral imagery requires large sets of ground measurements for calibrating the models that estimate soil properties. To avoid collecting such expensive data, we proposed a procedure including two steps that involves only legacy soil data that were collected over and?or around the study site: <i>1)</i> estimation of a soil property using a spectral index of the literature and <i>2)</i> standardisation of the estimated soil property using legacy soil data. This approach was tested for mapping clay contents in a Mediterranean region in which VNIR/SWIR AISA-DUAL hyperspectral airborne data were acquired. The spectral index was the one proposed by Levin et al (2007) using the spectral bands at 2209, 2133 and 2225 nm. Two legacy soil databases were tested as inputs of the procedure: the <i>Focused-Legacy</i> database composed of 67 soil samples collected in 2000 over the study area, and the No-Focused-Legacy database composed of 64 soil samples collected between 1973 and 1979 around but outside of the study area. The results were compared with those obtained from 120 soil samples collected over the study area during the hyperspectral airborne data acquisition, which were considered as a reference. <br><br> Our results showed that: <i>1)</i> the spectral index with no further standardisation offered predictions with high accuracy in term of coefficient of correlation <i>r</i> (0.71), but also high <i>bias</i> (&minus;414 g/kg) and <i>SEP</i> (439 g/kg), <i>2)</i> the standardisation using both legacy soil databases allowed an increase of accuracy (<i>r</i> = 0.76) and a reduction of <i>bias</i> and <i>SEP</i> and <i>3)</i> a better standardisation was obtained by using the <i>Focused-Legacy</i> database rather than the <i>No-Focused-Legacy</i> database. Finally, the clay predicted map obtained with standardisation using the <i>Focused-Legacy</i> database showed pedologically-significant soil spatial structures with clear short-scale variations of topsoil clay contents in specific areas. <br><br> This study, associated with the coming availability of a next generation of hyperspectral VNIR/SWIR satellite data for the entire globe, paves the way for inexpensive methods for delivering high resolution soil properties maps.

scholarly journals Hyperspectral Estimation Models of Winter Wheat Chlorophyll Content Under Elevated CO2

2021 ◽  
Vol 12 ◽  
Author(s):  
Yao Cai ◽  
Yuxuan Miao ◽  
Hao Wu ◽  
Dan Wang
Keyword(s):  
Winter Wheat ◽  
Chlorophyll Content ◽  
Spectral Reflectance ◽  
Vegetation Index ◽  
Estimation Model ◽  
Important Indicator ◽  
Spectral Bands ◽  
Close Relationship ◽  
The Relationship ◽  
Red Edge Position

Chlorophyll content is an important indicator of winter wheat health status. It is valuable to investigate whether the relationship between spectral reflectance and the chlorophyll content differs under elevated CO2 condition. In this open-top chamber experiment, the CO2 treatments were categorized into ambient (aCO2; about 400 μmol⋅mol–1) or elevated (eCO2; ambient + 200 μmol⋅mol–1) levels. The correlation between the spectral reflectance and the chlorophyll content of the winter wheat were analyzed by constructing the estimation model based on red edge position, sensitive band and spectral index methods, respectively. The results showed that there was a close relationship between chlorophyll content and the canopy spectral curve characteristics of winter wheat. Chlorophyll content was better estimated based on sensitive spectral bands and difference vegetation index (DVI) under both aCO2 and eCO2 conditions, though the accuracy of the models varied under different CO2 conditions. The results suggested that the hyperspectral measurement can be effectively used to estimate the chlorophyll content under both aCO2 and eCO2 conditionsand could provide a useful tool for monitoring plants physiology and growth.

scholarly journals Estimativas do Teor de Clorofila do Mangue da Baía de Vitória (ES) por meio de Dados Hiperespectrais

2020 ◽  
Vol 13 (1) ◽  
pp. 131
Author(s):  
Elizabeth Dell Orto e Silva ◽  
Monica Maria Pereira Tognella ◽  
Alexandre Candido Xavier ◽  
Gabriela Carvalho Zamprogno ◽  
Savia Soares Pascoalini
Keyword(s):  
Chlorophyll Content ◽  
Chlorophyll A ◽  
Spectral Index ◽  
Spectral Response ◽  
Field Measurements ◽  
Hyperspectral Data ◽  
Net Radiation ◽  
Mangrove Species ◽  
Spectral Bands ◽  
Red Edge

O teor de clorofila pode indicar a saúde geral da vegetação, e alterações no conteúdo do pigmento da folha podem ter uma relação direta com mudanças na resposta espectral da folha. O objetivo deste estudo é estimar o conteúdo de clorofila do manguezal da Baía de Vitória (ES) por meio de dados hiperespectrais. Foi analisado o comportamento espectral de duas espécies de mangue; R. mangle e L. racemosa utilizando um espectrorradiômetro, e realizadas medidas em campo dos índices de clorofila a, b e total a partir de um medidor eletrônico ClorofiLOG CFL-1030 (Falker). Os índices de clorofila das duas espécies de mangue foram correlacionados com os índices espectrais obtidos por meio de álgebra de bandas (λ1 + λ2 / λ1 - λ2), com a máxima reflectância da borda do vermelho (red edge) e bandas espectrais estreitas (350 nm a 2500 nm). Os índices criados a partir das bandas (391nm e 396nm) e (736nm e 821nm) apresentaram os maiores coeficientes de determinação quando correlacionados à clorofila a (r² 0,72) e clorofila b (r² 0,77) para a espécie L. racemosa. Para a espécie R. mangle, não foi possível identificar uma banda estreita ou um índice espectral que apresentasse alta correlação com os índices de clorofila a, b ou total. Os resultados apontam para a necessidade de caracterizar mais detalhadamente as condições ambientais, e também as condições biofísicas do bosque de mangue para obtenção de modelos de regressão precisos e específicos para cada espécie em particular. Estimates of Vitoria Bay Mangrove (ES) Chlorophyll Content by Hyperspectral Data A B S T R A C TThe chlorophyll content may indicate the general health of the vegetation, and alterations in the content of the leaf pigment may have a direct relation with changes in the spectral response of the leaf. The objective of this study is to estimate the chlorophyll content of the Vitória Bay mangrove (ES)  by means hyperspectral data. The spectral behavior of two mangrove species was analyzed; R. mangle and L. racemosa using a spectroradiometer, and field measurements of chlorophyll indices were performed with a ClorofiLOG CFL-1030 (Falker) electronic meter. The chlorophyll indices of the two mangrove species were correlated with the spectral indices obtained by means of band algebra (λ1 + λ2 / λ1 - λ2), and with the maximum red edge reflectance and narrow spectral bands ( 350 nm at 2500 nm). The indices created from the bands (391nm and 396nm) and (736nm and 821nm) presented the highest coefficients of determination when correlated to chlorophyll a (r ² 0.72) and chlorophyll b (r ² 0.77) for L. racemosa . For the R. mangle species, it was not possible to identify a narrow band or a spectral index that showed high correlation with the indexes of chlorophyll a, b or total. The results point to the need to characterize in more detail the environmental conditions, as well as the biophysical conditions of the mangrove forest to obtain accurate and specific regression models for each speciesKeywords: radiation, net radiation, photosynthetically active radiation, Caatinga, dry.Key words: Chlorophyll a, b and total, hyperspectral analysis, red edge, spectral index.

scholarly journals Spectral Feature Selection Optimization for Water Quality Estimation

2019 ◽  
Vol 17 (1) ◽  
pp. 272 ◽  
Author(s):  
Manh Van Nguyen ◽  
Chao-Hung Lin ◽  
Hone-Jay Chu ◽  
Lalu Muhamad Jaelani ◽  
Muhammad Aldila Syariz
Keyword(s):  
Near Infrared ◽  
Spectral Feature ◽  
Correlation Coefficients ◽  
Estimation Model ◽  
Chl A ◽  
Spectral Bands ◽  
Spectral Models ◽  
Multispectral Satellite Images ◽  
Estimation Models

The spatial heterogeneity and nonlinearity exhibited by bio-optical relationships in turbid inland waters complicate the retrieval of chlorophyll-a (Chl-a) concentration from multispectral satellite images. Most studies achieved satisfactory Chl-a estimation and focused solely on the spectral regions from near-infrared (NIR) to red spectral bands. However, the optical complexity of turbid waters may vary with locations and seasons, which renders the selection of spectral bands challenging. Accordingly, this study proposes an optimization process utilizing available spectral models to achieve optimal Chl-a retrieval. The method begins with the generation of a set of feature candidates, followed by candidate selection and optimization. Each candidate links to a Chl-a estimation model, including two-band, three-band, and normalized different chlorophyll index models. Moreover, a set of selected candidates using available spectral bands implies an optimal composition of estimation models, which results in an optimal Chl-a estimation. Remote sensing images and in situ Chl-a measurements in Lake Kasumigaura, Japan, are analyzed quantitatively and qualitatively to evaluate the proposed method. Results indicate that the model outperforms related Chl-a estimation models. The root-mean-squared errors of the Chl-a concentration obtained by the resulting model (OptiM-3) improve from 11.95 mg · m − 3 to 6.37 mg · m − 3 , and the Pearson’s correlation coefficients between the predicted and in situ Chl- a improve from 0.56 to 0.89.

scholarly journals Spectral Reflectance in Silver Birch Genotypes from Three Provenances in Finland

2020 ◽  
Vol 12 (17) ◽  
pp. 2677
Author(s):  
Maya Deepak ◽  
Sarita Keski-Saari ◽  
Laure Fauch ◽  
Lars Granlund ◽  
Elina Oksanen ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Chlorophyll Content ◽  
Spectral Reflectance ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Principal Component ◽  
Leaf Traits ◽  
Silver Birch ◽  
Red Edge

The goal of this study was to investigate the variation in the leaf spectral reflectance and its association with other leaf traits from 12 genotypes among three provenances of origin (populations) in a common garden for Finnish silver birch trees in 2015 and 2016. The spectral reflectance was measured in the laboratory from the detached leaves in the wavelength range of visible and near-infrared (VNIR, 400–1000 nm) and shortwave infrared (SWIR, 1000–2500 nm). The variation among the provenance was initially visualized with principal component analysis (PCA) and a clear separation among the provenances was detected with the discriminant analysis of principal components (DAPC) and partial least squares discriminant analysis (PLS-DA) depicting a less strong variation among the genotypes within the provenances. Wavelengths contributing to the separation of the genotypes and provenances were identified from the contribution plot of DAPC and the red edge was strongly related to the differences. Chlorophyll content showed clear provenance variation and was associated with the separation among the genotypes and provenances in the DAPC space. The normalized difference vegetation index (NDVI705,750) and chlorophyll reflectance index (CRI) showed clear significance among the provenances, whereas NDVI670,780 showed no variation. The variation in the chlorophyll content and the CRI and red edge-based NDVI indices indicated seasonal variation as the chlorophyll content starts increasing in early June. The correlation of foliar chlorophyll content and the chlorophyll-related spectral indices for the discrimination of provenances and genotypes are reported for the first time in a naturally occurring tree species consecutively for two years.

scholarly journals Water Relations, Hormonal Level, and Spectral Reflectance of Gerbera jamesonii BoluS Subjected to Chilling Stress

1995 ◽  
Vol 120 (3) ◽  
pp. 515-519 ◽  
Author(s):  
R. Savé ◽  
J. Peñuelas ◽  
I. Filella ◽  
C. Olivella
Keyword(s):  
Water Potential ◽  
Chlorophyll Content ◽  
Hydraulic Resistance ◽  
Leaf Water Potential ◽  
Spectral Reflectance ◽  
Near Infrared ◽  
Chilling Stress ◽  
Chilling Injury ◽  
Leaf Water ◽  
Initial Values

One-year-old gerbera plants subjected to 1 night at 5C had reduced leaf water losses and chlorophyll content and increased root hydraulic resistance, but stomatal conductance and leaf water potential did not change. After 3 nights, leaf water potential had decreased and leaf reflectance in the visible and the near-infrared had increased. Similarly, abscisic acid (ABA) in leaves had increased and cytokinins (CK) in leaves and roots had decreased, but ABA levels in roots did not change. After 4 days at 20C, root hydraulic resistance, reflectance and leaf water loss returned to their initial values, but leaf water potential and chlorophyll content remained lower. Leaf ABA levels reached values lower than the initial, while root ABA and leaf CK levels retained the initial values. These data suggest that in the gerbera plants studied, 3 nights at 5C produced a reversible strain but otherwise plants remained uninjured, so this gerbera variety could be cultured with low energetic inputs under Mediterranean conditions. The results may indicate that ABA and CK were acting as synergistic signals of the chilling stress. Spectral reflectance signals seemed to be useful as plant chilling injury indicators at ground level.

scholarly journals Understanding Vine Hyperspectral Signature through Different Irrigation Plans: A First Step to Monitor Vineyard Water Status

2021 ◽  
Vol 13 (3) ◽  
pp. 536
Author(s):  
Eve Laroche-Pinel ◽  
Mohanad Albughdadi ◽  
Sylvie Duthoit ◽  
Véronique Chéret ◽  
Jacques Rousseau ◽  
...  
Keyword(s):  
Near Infrared ◽  
Water Status ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Short Wave ◽  
Spatial And Temporal Scales ◽  
Spectral Bands ◽  
Main Challenge ◽  
Spectral Scale ◽  
Grape Varieties

The main challenge encountered by Mediterranean winegrowers is water management. Indeed, with climate change, drought events are becoming more intense each year, dragging the yield down. Moreover, the quality of the vineyards is affected and the level of alcohol increases. Remote sensing data are a potential solution to measure water status in vineyards. However, important questions are still open such as which spectral, spatial, and temporal scales are adapted to achieve the latter. This study aims at using hyperspectral measurements to investigate the spectral scale adapted to measure their water status. The final objective is to find out whether it would be possible to monitor the vine water status with the spectral bands available in multispectral satellites such as Sentinel-2. Four Mediterranean vine plots with three grape varieties and different water status management systems are considered for the analysis. Results show the main significant domains related to vine water status (Short Wave Infrared, Near Infrared, and Red-Edge) and the best vegetation indices that combine these domains. These results give some promising perspectives to monitor vine water status.

Use of spectral reflectance from a compact spectrometer to assess chlorophyll content in Zizania latifolia

2021 ◽  
pp. 1-13
Author(s):  
Rei Sonobe ◽  
Hiroto Yamashita ◽  
Adenan Yandra Nofrizal ◽  
Haruyuki Seki ◽  
Akio Morita ◽  
...  
Keyword(s):  
Chlorophyll Content ◽  
Spectral Reflectance ◽  
Zizania Latifolia
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