The Experts below are selected from a list of 5265 Experts worldwide ranked by ideXlab platform

Yanlian Zhou - One of the best experts on this subject based on the ideXlab platform.

  • performance of a two leaf Light Use Efficiency model for mapping gross primary productivity against remotely sensed sun induced chlorophyll fluorescence data
    Science of The Total Environment, 2018
    Co-Authors: Yanlian Zhou, Weimin Ju, Yongguang Zhang, Leiming Zhang
    Abstract:

    Estimating terrestrial gross primary production is an important task when studying the carbon cycle. In this study, the ability of a two-leaf Light Use Efficiency model to simulate regional gross primary production in China was validated using satellite Global Ozone Monitoring Instrument -2 sun-induced chlorophyll fluorescence data. The two-leaf Light Use Efficiency model was Used to estimate daily gross primary production in China's terrestrial ecosystems with 500-m resolution for the period from 2007 to 2014. Gross primary production simulated with the two-leaf Light Use Efficiency model was resampled to a spatial resolution of 0.5 degrees and then compared with sun-induced chlorophyll fluorescence. During the study period, sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf Light Use Efficiency model exhibited similar spatial and temporal patterns in China. The correlation coefficient between sun-induced chlorophyll fluorescence and monthly gross primary production simulated by the two-leaf Light Use Efficiency model was significant (p < 0.05, n = 96) in 88.9% of vegetated areas in China (average value 0.78) and varied among vegetation types. The interannual variations inmonthly sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf Light Use Efficiency model were similar in spring and autumn inmost vegetated regions, but dissimilar in winter and summer. The spatial variability of sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf Light Use Efficiency model was similar in spring, summer, and autumn. The proportion of spatial variations of sun-induced chlorophyll fluorescence and annual gross primary production simulated by the two-leaf Light Use Efficiency model explained by ranged from 0.76 (2011) to 0.80 (2013) during the study period. Overall, the two-leaf Light Use Efficiency model was capable of capturing spatial and temporal variations in gross primary production in China. However, the model needs further improvement to better simulate gross primary production in summer. (C) 2017 Elsevier B.V. All rights reserved.

  • Performance of a two-leaf Light Use Efficiency model for mapping gross primary productivity against remotely sensed sun-induced chlorophyll fluorescence data.
    The Science of the total environment, 2017
    Co-Authors: Yanlian Zhou, Weimin Ju, Yongguang Zhang, Leiming Zhang
    Abstract:

    Estimating terrestrial gross primary production is an important task when studying the carbon cycle. In this study, the ability of a two-leaf Light Use Efficiency model to simulate regional gross primary production in China was validated using satellite Global Ozone Monitoring Instrument - 2 sun-induced chlorophyll fluorescence data. The two-leaf Light Use Efficiency model was Used to estimate daily gross primary production in China's terrestrial ecosystems with 500-m resolution for the period from 2007 to 2014. Gross primary production simulated with the two-leaf Light Use Efficiency model was resampled to a spatial resolution of 0.5° and then compared with sun-induced chlorophyll fluorescence. During the study period, sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf Light Use Efficiency model exhibited similar spatial and temporal patterns in China. The correlation coefficient between sun-induced chlorophyll fluorescence and monthly gross primary production simulated by the two-leaf Light Use Efficiency model was significant (p

  • global parameterization and validation of a two leaf Light Use Efficiency model for predicting gross primary production across fluxnet sites
    Journal of Geophysical Research, 2016
    Co-Authors: Yanlian Zhou, Weimin Ju, Shaoqiang Wang, Huimin Wang, Andrew T Black, Wenping Yuan, Xiaocui Wu, Jing M Chen, Rachhpal S Jassal, Andreas Ibrom
    Abstract:

    Light Use Efficiency (LUE) models are widely Used to simulate gross primary production (GPP). However, the treatment of the plant canopy as a big leaf by these models can introduce large uncertainties in simulated GPP. Recently, a two-leaf Light Use Efficiency (TL-LUE) model was developed to simulate GPP separately for sunlit and shaded leaves and has been shown to outperform the big-leaf MOD17 model at six FLUX sites in China. In this study we investigated the performance of the TL-LUE model for a wider range of biomes. For this we optimized the parameters and tested the TL-LUE model using data from 98 FLUXNET sites which are distributed across the globe. The results showed that the TL-LUE model performed in general better than the MOD17 model in simulating 8 day GPP. Optimized maximum Light Use Efficiency of shaded leaves (epsilon(msh)) was 2.63 to 4.59 times that of sunlit leaves (epsilon(msu)). Generally, the relationships of epsilon(msh) and epsilon(msu) with epsilon(max) were well described by linear equations, indicating the existence of general patterns across biomes. GPP simulated by the TL-LUE model was much less sensitive to biases in the photosynthetically active radiation (PAR) input than the MOD17 model. The results of this study suggest that the proposed TL-LUE model has the potential for simulating regional and global GPP of terrestrial ecosystems, and it is more robust with regard to usual biases in input data than existing approaches which neglect the bimodal within-canopy distribution of PAR.

  • development of a two leaf Light Use Efficiency model for improving the calculation of terrestrial gross primary productivity
    Agricultural and Forest Meteorology, 2013
    Co-Authors: Yanlian Zhou, Weimin Ju, Shaoqiang Wang, Mingzhu He, Jingming Chen, Honglin He, Huimin Wang
    Abstract:

    Gross primary productivity (GPP) is a key component of land atmospheric carbon exchange. Reliable calculation of regional/global GPP is crucial for understanding the response of terrestrial ecosystems to climate change and human activity. In recent years, many Light Use Efficiency (LUE) models driven by remote sensing data have been developed for calculating GPP at various spatial and temporal scales. However, some studies show that GPP calculated by LUE models was biased by different degrees depending on sky clearness conditions. In this study, a two-leaf Light Use Efficiency (TL-LUE) model is developed based on the MOD 17 algorithm to improve the calculation of GPP. This TL-LUE model separates the canopy into sunlit and shaded leaf groups and calculates GPP separately for them with different maximum Light Use efficiencies. Different algorithms are developed to calculate the absorbed photosynthetically active radiation for these two groups. GPP measured at 6 typical ecosystems in China was Used to calibrate and validate the model. The results show that with the calibration using tower measurements of GPP, the MOD17 algorithm was able to capture the variations of measured GPP in different seasons and sites. But it tends to understate and overestimate GPP under the conditions of low and high sky clearness, respectively. The new TL-LUE model outperforms the MOD17 algorithm in reproducing measured GPP at daily and 8-day scales, especially at forest sites. The calibrated LUE of shaded leaves is 2.5-3.8 times larger than that of sunlit leaves. The newly developed TL-LUE model shows lower sensitivity to sky conditions than the MOD17 algorithm. This study demonstrates the potential of the TL-LUE model in improving GPP calculation due to proper description of differences in the LUE of sunlit and shaded leaves and in the transfer of direct and diffUse Light beams within the canopy. (C) 2013 Elsevier B.V. All rights reserved.

Weimin Ju - One of the best experts on this subject based on the ideXlab platform.

  • performance of a two leaf Light Use Efficiency model for mapping gross primary productivity against remotely sensed sun induced chlorophyll fluorescence data
    Science of The Total Environment, 2018
    Co-Authors: Yanlian Zhou, Weimin Ju, Yongguang Zhang, Leiming Zhang
    Abstract:

    Estimating terrestrial gross primary production is an important task when studying the carbon cycle. In this study, the ability of a two-leaf Light Use Efficiency model to simulate regional gross primary production in China was validated using satellite Global Ozone Monitoring Instrument -2 sun-induced chlorophyll fluorescence data. The two-leaf Light Use Efficiency model was Used to estimate daily gross primary production in China's terrestrial ecosystems with 500-m resolution for the period from 2007 to 2014. Gross primary production simulated with the two-leaf Light Use Efficiency model was resampled to a spatial resolution of 0.5 degrees and then compared with sun-induced chlorophyll fluorescence. During the study period, sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf Light Use Efficiency model exhibited similar spatial and temporal patterns in China. The correlation coefficient between sun-induced chlorophyll fluorescence and monthly gross primary production simulated by the two-leaf Light Use Efficiency model was significant (p < 0.05, n = 96) in 88.9% of vegetated areas in China (average value 0.78) and varied among vegetation types. The interannual variations inmonthly sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf Light Use Efficiency model were similar in spring and autumn inmost vegetated regions, but dissimilar in winter and summer. The spatial variability of sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf Light Use Efficiency model was similar in spring, summer, and autumn. The proportion of spatial variations of sun-induced chlorophyll fluorescence and annual gross primary production simulated by the two-leaf Light Use Efficiency model explained by ranged from 0.76 (2011) to 0.80 (2013) during the study period. Overall, the two-leaf Light Use Efficiency model was capable of capturing spatial and temporal variations in gross primary production in China. However, the model needs further improvement to better simulate gross primary production in summer. (C) 2017 Elsevier B.V. All rights reserved.

  • Performance of a two-leaf Light Use Efficiency model for mapping gross primary productivity against remotely sensed sun-induced chlorophyll fluorescence data.
    The Science of the total environment, 2017
    Co-Authors: Yanlian Zhou, Weimin Ju, Yongguang Zhang, Leiming Zhang
    Abstract:

    Estimating terrestrial gross primary production is an important task when studying the carbon cycle. In this study, the ability of a two-leaf Light Use Efficiency model to simulate regional gross primary production in China was validated using satellite Global Ozone Monitoring Instrument - 2 sun-induced chlorophyll fluorescence data. The two-leaf Light Use Efficiency model was Used to estimate daily gross primary production in China's terrestrial ecosystems with 500-m resolution for the period from 2007 to 2014. Gross primary production simulated with the two-leaf Light Use Efficiency model was resampled to a spatial resolution of 0.5° and then compared with sun-induced chlorophyll fluorescence. During the study period, sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf Light Use Efficiency model exhibited similar spatial and temporal patterns in China. The correlation coefficient between sun-induced chlorophyll fluorescence and monthly gross primary production simulated by the two-leaf Light Use Efficiency model was significant (p

  • Application of the photochemical reflectance index to track Light Use Efficiency with a two-leaf model
    2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
    Co-Authors: Qian Zhang, Weimin Ju, Jing M Chen, Fengting Yang
    Abstract:

    Proper determination of Light Use Efficiency (LUE) is a prerequisite for LUE models to simulate gross primary productivity (GPP). This study was devoted to apply the photochemical reflectance index (PRI) to accurately track LUE variations for a sub-tropical coniferous forest using tower-based PRI and GPP measurements. To improve the ability of PRI to track LUE, a simple two-leaf approach is Used to process the remote sensing and flux data. The results showed: both PRI and LUE decreased with increases of bioclimatic factors. PRI is able to capture diurnal and seasonal changes in LUE. And the two-leaf approach significantly enhanced the correlation between PRI and LUE at either half-hourly or daily time steps.

  • IGARSS - Application of the photochemical reflectance index to track Light Use Efficiency with a two-leaf model
    2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
    Co-Authors: Qian Zhang, Weimin Ju, Jing M Chen, Fengting Yang
    Abstract:

    Proper determination of Light Use Efficiency (LUE) is a prerequisite for LUE models to simulate gross primary productivity (GPP). This study was devoted to apply the photochemical reflectance index (PRI) to accurately track LUE variations for a sub-tropical coniferous forest using tower-based PRI and GPP measurements. To improve the ability of PRI to track LUE, a simple two-leaf approach is Used to process the remote sensing and flux data. The results showed: both PRI and LUE decreased with increases of bioclimatic factors. PRI is able to capture diurnal and seasonal changes in LUE. And the two-leaf approach significantly enhanced the correlation between PRI and LUE at either half-hourly or daily time steps.

  • global parameterization and validation of a two leaf Light Use Efficiency model for predicting gross primary production across fluxnet sites
    Journal of Geophysical Research, 2016
    Co-Authors: Yanlian Zhou, Weimin Ju, Shaoqiang Wang, Huimin Wang, Andrew T Black, Wenping Yuan, Xiaocui Wu, Jing M Chen, Rachhpal S Jassal, Andreas Ibrom
    Abstract:

    Light Use Efficiency (LUE) models are widely Used to simulate gross primary production (GPP). However, the treatment of the plant canopy as a big leaf by these models can introduce large uncertainties in simulated GPP. Recently, a two-leaf Light Use Efficiency (TL-LUE) model was developed to simulate GPP separately for sunlit and shaded leaves and has been shown to outperform the big-leaf MOD17 model at six FLUX sites in China. In this study we investigated the performance of the TL-LUE model for a wider range of biomes. For this we optimized the parameters and tested the TL-LUE model using data from 98 FLUXNET sites which are distributed across the globe. The results showed that the TL-LUE model performed in general better than the MOD17 model in simulating 8 day GPP. Optimized maximum Light Use Efficiency of shaded leaves (epsilon(msh)) was 2.63 to 4.59 times that of sunlit leaves (epsilon(msu)). Generally, the relationships of epsilon(msh) and epsilon(msu) with epsilon(max) were well described by linear equations, indicating the existence of general patterns across biomes. GPP simulated by the TL-LUE model was much less sensitive to biases in the photosynthetically active radiation (PAR) input than the MOD17 model. The results of this study suggest that the proposed TL-LUE model has the potential for simulating regional and global GPP of terrestrial ecosystems, and it is more robust with regard to usual biases in input data than existing approaches which neglect the bimodal within-canopy distribution of PAR.

Leiming Zhang - One of the best experts on this subject based on the ideXlab platform.

  • performance of a two leaf Light Use Efficiency model for mapping gross primary productivity against remotely sensed sun induced chlorophyll fluorescence data
    Science of The Total Environment, 2018
    Co-Authors: Yanlian Zhou, Weimin Ju, Yongguang Zhang, Leiming Zhang
    Abstract:

    Estimating terrestrial gross primary production is an important task when studying the carbon cycle. In this study, the ability of a two-leaf Light Use Efficiency model to simulate regional gross primary production in China was validated using satellite Global Ozone Monitoring Instrument -2 sun-induced chlorophyll fluorescence data. The two-leaf Light Use Efficiency model was Used to estimate daily gross primary production in China's terrestrial ecosystems with 500-m resolution for the period from 2007 to 2014. Gross primary production simulated with the two-leaf Light Use Efficiency model was resampled to a spatial resolution of 0.5 degrees and then compared with sun-induced chlorophyll fluorescence. During the study period, sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf Light Use Efficiency model exhibited similar spatial and temporal patterns in China. The correlation coefficient between sun-induced chlorophyll fluorescence and monthly gross primary production simulated by the two-leaf Light Use Efficiency model was significant (p < 0.05, n = 96) in 88.9% of vegetated areas in China (average value 0.78) and varied among vegetation types. The interannual variations inmonthly sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf Light Use Efficiency model were similar in spring and autumn inmost vegetated regions, but dissimilar in winter and summer. The spatial variability of sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf Light Use Efficiency model was similar in spring, summer, and autumn. The proportion of spatial variations of sun-induced chlorophyll fluorescence and annual gross primary production simulated by the two-leaf Light Use Efficiency model explained by ranged from 0.76 (2011) to 0.80 (2013) during the study period. Overall, the two-leaf Light Use Efficiency model was capable of capturing spatial and temporal variations in gross primary production in China. However, the model needs further improvement to better simulate gross primary production in summer. (C) 2017 Elsevier B.V. All rights reserved.

  • Performance of a two-leaf Light Use Efficiency model for mapping gross primary productivity against remotely sensed sun-induced chlorophyll fluorescence data.
    The Science of the total environment, 2017
    Co-Authors: Yanlian Zhou, Weimin Ju, Yongguang Zhang, Leiming Zhang
    Abstract:

    Estimating terrestrial gross primary production is an important task when studying the carbon cycle. In this study, the ability of a two-leaf Light Use Efficiency model to simulate regional gross primary production in China was validated using satellite Global Ozone Monitoring Instrument - 2 sun-induced chlorophyll fluorescence data. The two-leaf Light Use Efficiency model was Used to estimate daily gross primary production in China's terrestrial ecosystems with 500-m resolution for the period from 2007 to 2014. Gross primary production simulated with the two-leaf Light Use Efficiency model was resampled to a spatial resolution of 0.5° and then compared with sun-induced chlorophyll fluorescence. During the study period, sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf Light Use Efficiency model exhibited similar spatial and temporal patterns in China. The correlation coefficient between sun-induced chlorophyll fluorescence and monthly gross primary production simulated by the two-leaf Light Use Efficiency model was significant (p

F G Hall - One of the best experts on this subject based on the ideXlab platform.

  • inferring terrestrial photosynthetic Light Use Efficiency of temperate ecosystems from space
    Journal of Geophysical Research, 2011
    Co-Authors: Nicholas C. Coops, Thomas Hilker, F G Hall, Caroline Nichol, Andrew T Black, Alexei Lyapustin, Michael A Wulder
    Abstract:

    [1] Terrestrial ecosystems absorb about 2.8 Gt C yr?1, which is estimated to be about a quarter of the carbon emitted from fossil fuel combustion. However, the uncertainties of this sink are large, on the order of ±40%, with spatial and temporal variations largely unknown. One of the largest factors contributing to the uncertainty is photosynthesis, the process by which plants absorb carbon from the atmosphere. Currently, photosynthesis, or gross ecosystem productivity (GEP), can only be inferred from flux towers by measuring the exchange of CO2 in the surrounding air column. Consequently, carbon models suffer from a lack of spatial coverage of accurate GEP observations. Here, we show that photosynthetic Light Use Efficiency (?), hence photosynthesis, can be directly inferred from spaceborne measurements of reflectance. We demonstrate that the differential between reflectance measurements in bands associated with the vegetation xanthophyll cycle and estimates of canopy shading obtained from multiangular satellite observations (using the CHRIS/PROBA sensor) permits us to infer plant photosynthetic Efficiency, independently of vegetation type and structure (r2 = 0.68, compared to flux measurements). This is a significant advance over previous approaches seeking to model global-scale photosynthesis indirectly from a combination of growth limiting factors, most notably pressure deficit and temperature. When combined with modeled global-scale photosynthesis, satellite-inferred ? can improve model estimates through data assimilation. We anticipate that our findings will guide the development of new spaceborne approaches to observe vegetation carbon uptake and improve current predictions of global CO2 budgets and future climate scenarios by providing regularly timed calibration points for modeling plant photosynthesis consistently at a global scale.

  • remote sensing of photosynthetic Light Use Efficiency across two forested biomes spatial scaling
    Remote Sensing of Environment, 2010
    Co-Authors: Thomas Hilker, Nicholas C. Coops, Zoran Nesic, F G Hall, Alexei Lyapustin, Yujie Wang, Nicholas J Grant
    Abstract:

    Abstract Eddy covariance (EC) measurements have greatly advanced our knowledge of carbon exchange in terrestrial ecosystems. However, appropriate techniques are required to upscale these spatially discrete findings globally. Satellite remote sensing provides unique opportunities in this respect, but remote sensing of the photosynthetic Light-Use Efficiency (e), one of the key components of Gross Primary Production, is challenging. Some progress has been made in recent years using the photochemical reflectance index, a narrow waveband index centered at 531 and 570 nm. The high sensitivity of this index to various extraneous effects such as canopy structure, and the view observer geometry has so far prevented its Use at landscape and global scales. One critical aspect of upscaling PRI is the development of generic algorithms to account for structural differences in vegetation. Building on previous work, this study compares the differences in the PRI: ɛ relationship between a coastal Douglas-fir forest located on Vancouver Island, British Columbia, and a mature Aspen stand located in central Saskatchewan, Canada. Using continuous, tower-based observations acquired from an automated multi-angular spectro-radiometer (AMSPEC II) installed at each site, we demonstrate that PRI can be Used to measure ɛ throughout the vegetation season at the DF-49 stand (r2 = 0.91, p

  • estimation of Light Use Efficiency of terrestrial ecosystems from space a status report
    BioScience, 2010
    Co-Authors: Nicholas C. Coops, Thomas Hilker, F G Hall, Caroline Nichol, Guillaume Drolet
    Abstract:

    A critical variable in the estimation of gross primary production of terrestrial ecosystems is Light-Use Efficiency (LUE), a value that represents the actual Efficiency of a plant’s Use of absorbed radiation energy to produce biomass. Light-Use Efficiency is driven by the most limiting of a number of environmental stress factors that reduce plants’ photosynthetic capacity; these include short-term stressors, such as photoinhibition, as well as longer-term stressors, such as soil water and temperature. Modeling LUE from remote sensing is governed largely by the biochemical composition of plant foliage, with the past decade seeing important theoretical and modeling advances for understanding the role of these stresses on LUE. In this article we provide a summary of the tower-, aircraft-, and satellite-based research undertaken to date, and discuss the broader scalability of these methods, concluding with recommendations for ongoing research possibilities.

  • Determining ecosystem Light Use Efficiency for carbon exchange from satellite
    Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, 2005
    Co-Authors: K. Fred Huemmrich, F G Hall, Guillaume Drolet, Elizabeth M. Middleton, Hank A. Margolis, Robert G. Knox
    Abstract:

    Understanding the dynamics of the global carbon cycle requires an accurate determination of the spatial and temporal distribution of photosynthetic CO2 uptake by terrestrial vegetation. Stress factors may caUse sub-optimal photosynthetic function resulting in down-regulation (i.e., reduced rate of photosynthesis). Photosynthetic down-regulation is related to changes in the apparent spectral reflectance of leaves. Present approaches to determine ecosystem carbon exchange rely on meteorological data as inputs to models that predict the relative photosynthetic function in response to environmental conditions inducing stress (e.g., drought, high/low temperatures). This study examines the determination of ecosystem photosynthetic Light Use Efficiency (LUE) from satellite observations, through measurement of vegetation spectral reflectance changes associated with physiologic stress responses. This approach is possible using the Moderate-Resolution Spectroradiometer (MODIS) on Terra to provide frequent, narrow-band measurements of high radiometric accuracy. Data from reflective MODIS ocean bands were Used over land to calculate the Photochemical Reflectance Index (PRI), an index that is sensitive to reflectance changes near 531nm associated with vegetation stress responses exhibited by photosynthetic pigments. MODIS PRI values were compared with LUE calculated from values of CO2 flux measured at the overpass time at a flux tower located in a Douglas fir forest on Vancouver Island in Canada. Preliminary results show a relationship between MODIS PRI and LUE when using MODIS observations in the backscattering direction. These results compare well to previous work at a boreal aspen forest suggesting this approach may be generally Useful.

  • remote sensing of photosynthetic Light Use Efficiency of boreal forest
    Agricultural and Forest Meteorology, 2000
    Co-Authors: Caroline Nichol, Karl Huemmrich, Andrew T Black, P G Jarvis, C L Walthall, John Grace, F G Hall
    Abstract:

    Using a helicopter-mounted portable spectroradiometer and continuous eddy covariance data we were able to evaluate the photochemical reflectance index (PRI) as an indicator of canopy photosynthetic Light-Use Efficiency (LUE) in four boreal forest species during the Boreal Ecosystem Atmosphere experiment (BOREAS). PRI was calculated from narrow waveband reflectance data and correlated with LUE calculated from eddy covariance data. Significant linear correlations were found between PRI and LUE when the four species were grouped together and when divided into functional type: coniferous and deciduous. Data from the helicopter-mounted spectroradiometer were then averaged to represent data generated by the Airborne Visible Infrared Imaging Spectrometer (AVIRIS). We calculated PRI from these data and relationships with canopy LUE were investigated. The relationship between PRI and LUE was weakened for deciduous species but strengthened for the coniferous species. The robust nature of this relationship suggests that relative photosynthetic rates may be derived from remotely-sensed reflectance measurements. ©2000 Elsevier Science B.V. All rights reserved.

Thomas Hilker - One of the best experts on this subject based on the ideXlab platform.

  • Remote sensing of seasonal Light Use Efficiency in temperate bog ecosystems.
    Scientific Reports, 2017
    Co-Authors: Riccardo Tortini, Nicholas C. Coops, Zoran Nesic, Andreas Christen, Thomas Hilker
    Abstract:

    Despite storing approximately half of the atmosphere’s carbon, estimates of fluxes between wetlands and atmosphere under current and future climates are associated with large uncertainties, and it remains a challenge to determine human impacts on the net greenhoUse gas balance of wetlands at the global scale. In this study we demonstrate that the relationship between photochemical reflectance index, derived from high spectral and temporal multi-angular observations, and vegetation Light Use Efficiency was strong (r2 = 0.64 and 0.58 at the hotspot and darkspot, respectively), and can be utilized to estimate carbon fluxes from remote at temperate bog ecosystems. These results improve our understanding of the interactions between vegetation physiology and spectral characteristics to understand seasonal magnitudes and variations in Light Use Efficiency, opening new perspectives on the potential of this technique over extensive areas with different landcover.

  • inferring terrestrial photosynthetic Light Use Efficiency of temperate ecosystems from space
    Journal of Geophysical Research, 2011
    Co-Authors: Nicholas C. Coops, Thomas Hilker, F G Hall, Caroline Nichol, Andrew T Black, Alexei Lyapustin, Michael A Wulder
    Abstract:

    [1] Terrestrial ecosystems absorb about 2.8 Gt C yr?1, which is estimated to be about a quarter of the carbon emitted from fossil fuel combustion. However, the uncertainties of this sink are large, on the order of ±40%, with spatial and temporal variations largely unknown. One of the largest factors contributing to the uncertainty is photosynthesis, the process by which plants absorb carbon from the atmosphere. Currently, photosynthesis, or gross ecosystem productivity (GEP), can only be inferred from flux towers by measuring the exchange of CO2 in the surrounding air column. Consequently, carbon models suffer from a lack of spatial coverage of accurate GEP observations. Here, we show that photosynthetic Light Use Efficiency (?), hence photosynthesis, can be directly inferred from spaceborne measurements of reflectance. We demonstrate that the differential between reflectance measurements in bands associated with the vegetation xanthophyll cycle and estimates of canopy shading obtained from multiangular satellite observations (using the CHRIS/PROBA sensor) permits us to infer plant photosynthetic Efficiency, independently of vegetation type and structure (r2 = 0.68, compared to flux measurements). This is a significant advance over previous approaches seeking to model global-scale photosynthesis indirectly from a combination of growth limiting factors, most notably pressure deficit and temperature. When combined with modeled global-scale photosynthesis, satellite-inferred ? can improve model estimates through data assimilation. We anticipate that our findings will guide the development of new spaceborne approaches to observe vegetation carbon uptake and improve current predictions of global CO2 budgets and future climate scenarios by providing regularly timed calibration points for modeling plant photosynthesis consistently at a global scale.

  • remote sensing of photosynthetic Light Use Efficiency across two forested biomes spatial scaling
    Remote Sensing of Environment, 2010
    Co-Authors: Thomas Hilker, Nicholas C. Coops, Zoran Nesic, F G Hall, Alexei Lyapustin, Yujie Wang, Nicholas J Grant
    Abstract:

    Abstract Eddy covariance (EC) measurements have greatly advanced our knowledge of carbon exchange in terrestrial ecosystems. However, appropriate techniques are required to upscale these spatially discrete findings globally. Satellite remote sensing provides unique opportunities in this respect, but remote sensing of the photosynthetic Light-Use Efficiency (e), one of the key components of Gross Primary Production, is challenging. Some progress has been made in recent years using the photochemical reflectance index, a narrow waveband index centered at 531 and 570 nm. The high sensitivity of this index to various extraneous effects such as canopy structure, and the view observer geometry has so far prevented its Use at landscape and global scales. One critical aspect of upscaling PRI is the development of generic algorithms to account for structural differences in vegetation. Building on previous work, this study compares the differences in the PRI: ɛ relationship between a coastal Douglas-fir forest located on Vancouver Island, British Columbia, and a mature Aspen stand located in central Saskatchewan, Canada. Using continuous, tower-based observations acquired from an automated multi-angular spectro-radiometer (AMSPEC II) installed at each site, we demonstrate that PRI can be Used to measure ɛ throughout the vegetation season at the DF-49 stand (r2 = 0.91, p

  • estimation of Light Use Efficiency of terrestrial ecosystems from space a status report
    BioScience, 2010
    Co-Authors: Nicholas C. Coops, Thomas Hilker, F G Hall, Caroline Nichol, Guillaume Drolet
    Abstract:

    A critical variable in the estimation of gross primary production of terrestrial ecosystems is Light-Use Efficiency (LUE), a value that represents the actual Efficiency of a plant’s Use of absorbed radiation energy to produce biomass. Light-Use Efficiency is driven by the most limiting of a number of environmental stress factors that reduce plants’ photosynthetic capacity; these include short-term stressors, such as photoinhibition, as well as longer-term stressors, such as soil water and temperature. Modeling LUE from remote sensing is governed largely by the biochemical composition of plant foliage, with the past decade seeing important theoretical and modeling advances for understanding the role of these stresses on LUE. In this article we provide a summary of the tower-, aircraft-, and satellite-based research undertaken to date, and discuss the broader scalability of these methods, concluding with recommendations for ongoing research possibilities.