There is an increasing need to consistently combine observations from different sensors to monito... more There is an increasing need to consistently combine observations from different sensors to monitor the state of the land surface. In order to achieve this, robust methods based on the inversion of radiative transfer (RT) models can be used to interpret the satellite observations. This typically results in an inverse problem, but a major drawback of these methods is the computational complexity. We introduce the concept of Gaussian Process (GP) emulators: surrogate functions that accurately approximate RT models using a small set of input (e.g., leaf area index, leaf chlorophyll, etc.) and output (e.g., top-of-canopy reflectances or at sensor radiances) pairs. The emulators quantify the uncertainty of their approximation, and provide a fast and easy route to estimating the Jacobian of the original model, enabling the use of e.g., efficient gradient descent methods. We demonstrate the emulation of widely used RT models (PROSAIL and SEMIDISCRETE) and the coupling of vegetation and atmospheric (6S) RT models targetting particular sensor bands. A comparison with the full original model outputs shows that the emulators are a viable option to replace the original model, with negligible bias and discrepancies which are much smaller than the typical uncertainty in the observations. We also extend the theory of GP to cope with models with multivariate outputs (e.g., over the full solar reflective domain), and apply this to the emulation of PROSAIL, coupled 6S and PROSAIL and to the emulation of individual spectral components of 6S. In all cases, emulators successfully predict the full model output as well as accurately predict the gradient of the model calculated by finite differences, and produce speed ups between 10,000 and 50,000 times that of the original model. Finally, we use emulators to invert leaf area index (LAI), leaf chlorophyll content (C ab) and equivalent leaf water thickness (C w) from a time series of observations from Sentinel-2/MSI, Sentinel-3/SLSTR and Proba-V observations. We use sophisticated Hamiltonian Markov Chain Monte Carlo (MCMC) methods that exploit the speed of the emulators as well as the gradient estimation, a variational data assimilation (DA) method that extends the problem with temporal regularisation, and a particle filter using a regularisation model. The variational and particle filter approach appear more successful (meaning parameters closer to the truth, and smaller uncertainties) than the MCMC approach as a result of using the temporal regularisation mode. These work therefore suggests that GP emulators are a practical way to implement sophisticated parameter retrieval schemes in an era of increasing data volumes.
IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174), 1998
A fieldwork campaign was undertaken in East Anglia, UK (52" 37.2' N 0" 32.0' E), during the winte... more A fieldwork campaign was undertaken in East Anglia, UK (52" 37.2' N 0" 32.0' E), during the winter/spring growing season of 1997. Manual structural measurements were made of individual plants from a variety of crops in order to allow detailed geometric representations of these plants to be constructed within the Botanical Plant Modelling System (BPMS) [1] [2] with the aim of exploring and validating the extraction of canopy structural information from a variety of remotely sensed data. Results are presented from simulations carried out using BPMS data of barley crops at a variety of stages of growth. Measured directional reflectance data are compared with BPMS simulations, and derived structural parameters (LAI, %age cover) compared with independent measurements made in the field. Results show that the derived reflectance values are generally in good agreement with those obtained by direct measurement, whilst the %age cover and LAI values are more variable. This may be due to the difficulty of characterising inherently variable parameters with limited manual measurements.
Satellite monitoring of disturbances in Arctic ecosystems
International Geoscience and Remote Sensing Symposium (IGARSS), 2009
Abstract This study explores the capability of satellite remote sensing to detect relatively rapi... more Abstract This study explores the capability of satellite remote sensing to detect relatively rapid changes of vegetation cover in northern Fennoscandian regions in response to disturbance more generally, and insect defoliation damage in particular. The data used is a long term time series of leaf area index (LAI) at 8 Km resolution derived from the Advanced Very High Resolution Radiometer (AVHRR) between 1982 and 2006, developed to be structurally consistent with the Moderate Resolution Imaging Spectrometer (MODIS) ...
Global albedo, BRDF and nadir BRDF-adjusted reflectance products from MODIS
IEEE International Geoscience and Remote Sensing Symposium, 2002
Annual sequences of the first reprocessed albedo, bidirectional reflectance distribution function... more Annual sequences of the first reprocessed albedo, bidirectional reflectance distribution function (BRDF), and nadir BRDF-adjusted surface reflectance (NBAR) products are being evaluated. BRDF model parameters (or weights) are used to compute black sky albedo at local solar noon and white sky albedo and to compute surface reflectance at a common nadir geometry. In addition to these standard resolution albedo, BRDF,
A global data set of cloud occurrence probability derived from Moderate Resolution Imaging Spectr... more A global data set of cloud occurrence probability derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua gridded daily data is analyzed to investigate the probability of obtaining at least a minimum number of cloud-free observations within various compositing periods. The probabilities derived from Terra and Aqua, with morning and afternoon overpass times, respectively, are similar and increase with compositing period. Compositing both Terra and Aqua observations results in considerably higher probabilities of obtaining a sufficient number of observations for bidirectional reflectance model-based compositing. Given that the only alternative to obtaining sufficient samples is to extend the observation period, which can cause significant problems when the surface state changes, it is concluded that using data from the two MODIS sensors provides the most effective way of generating composited products. Findings with respect to the availability of cloud-free composites when n-day composites are generated on a temporally overlapping daily rolling basis, i.e., every day, rather than every n-days, are also discussed for regional and global applications.
On canopy spectral invariants and hyperspectral ray tracing
ABSTRACT In this paper we present a method for the efficient simulation of canopy hyperspectral r... more ABSTRACT In this paper we present a method for the efficient simulation of canopy hyperspectral reflectance using Monte Carlo Ray Tracing. The method essentially describes the scattered radiation in terms of spectral invariants that gives an expression as a series of powers of leaf single scattering albedo. This can then be post-processed to describe the scattering regime for arbitrary leaf spectral functions. The spectral invariant expression is explored to interpret some of its features. Some practical uses of this include the use of truncated ray tracing methods that can be adjusted for unsampled scattering orders by consideration of energy conservation.
Estimating land surface albedo in the HAPEX-Sahel experiment: model-based inversions using ASAS
Results are presented of spectral directional-hemispherical reflectance data derived from multi-l... more Results are presented of spectral directional-hemispherical reflectance data derived from multi-look angle airborne imagery over HAPEX-Sahel in 1992, along with the spatial distribution of BRDF parameters for a kernel-driven model. The results and techniques discussed are relevant to albedo derivation from data of this sort from both airborne and forthcoming satellite sensors
Biophysical parameter retrieval from forest and crop canopies in the optical and microwave domains using 3D models of canopy structure
... P. Saich, P. Lewis and MI Disney Centre for Terrestrial Carbon Dynamics Dept. ... The basis o... more ... P. Saich, P. Lewis and MI Disney Centre for Terrestrial Carbon Dynamics Dept. ... The basis of the technique is (i) a representation of the dynamic 3D structure of vegetation that can be used to drive (ii) numerical models of optical canopy reflectance (drat) and microwave ...
Comparison of Discrete Return and Waveform Airborne Lidar Derived Estimates of Fractional Cover in an Australian Savanna
ABSTRACT The advance of commercial airborne lidar systems from discrete-return to waveform record... more ABSTRACT The advance of commercial airborne lidar systems from discrete-return to waveform recording instruments has made repeatable estimates of biophysical variables from these different methods questionable. Using an experimental airborne waveform lidar dataset acquired in an Australian savanna, this study presents a method for the derivation of canopy/ground backscatter coefficients from waveform lidar and a comparison of discrete return and waveform approaches to the estimation of fractional cover. Despite limited validation, the results indicate that waveform estimates of fractional cover can provide consistently higher accuracy than discrete return estimates under varying survey properties. Ongoing work using raw waveform data across larger areas and 3D radiative transfer simulations aims to develop a quantitative understanding of the impact of disparate sensor and survey properties on the detection of change in vegetation structure using commercial lidar instruments.
The FLuorescence EXplorer (FLEX) mission proposes to launch a satellite for the global monitoring... more The FLuorescence EXplorer (FLEX) mission proposes to launch a satellite for the global monitoring of steady-state chlorophyll fluorescence in terrestrial vegetation. Fluorescence is a sensitive probe of photosynthetic function in both healthy and physiologically perturbed vegetation, and a powerful non-invasive tool to track the status, resilience, and recovery of photochemical processes and moreover provides important information on overall photosynthetic performance with implications for related carbon sequestration. The early responsiveness of fluorescence to atmospheric, soil and plant water balance, as well as to atmospheric chemistry and human intervention in land usage makes it an obvious biological indicator in improving our understanding of Earth system dynamics. The amenability of fluorescence to remote, even space-based observation qualifies it to join the emerging suite of space-based technologies for Earth observation. FLEX would encompass a three-instrument array for m...
The FLuorescence EXplorer (FLEX) mission proposes to launch a satellite for the global monitoring... more The FLuorescence EXplorer (FLEX) mission proposes to launch a satellite for the global monitoring of steady-state chlorophyll fluorescence in terrestrial vegetation. Fluorescence is a sensitive probe of photosynthetic function in both healthy and physiologically perturbed vegetation, and a powerful non-invasive tool to track the status, resilience, and recovery of photochemical processes and moreover provides important information on overall photosynthetic performance with implications for related carbon sequestration. The early responsiveness of fluorescence to atmospheric, soil and plant water balance, as well as to atmospheric chemistry and human intervention in land usage makes it an obvious biological indicator in improving our understanding of Earth system dynamics. The amenability of fluorescence to remote, even space-based observation qualifies it to join the emerging suite of space-based technologies for Earth observation. FLEX would encompass a three-instrument array for m...
Accurate terrestrial biosphere model (TBM) simulations of gross carbon uptake (gross primary prod... more Accurate terrestrial biosphere model (TBM) simulations of gross carbon uptake (gross primary productivity – GPP) are essential for reliable future terrestrial carbon sink projections. However, uncertainties in TBM GPP estimates remain. Newly-available satellite-derived sun-induced chlorophyll fluorescence (SIF) data offer a promising direction for addressing this issue by constraining regional-to-global scale modelled GPP. Here, we use monthly 0.5° GOME-2 SIF data from 2007 to 2011 to optimise GPP parameters of the ORCHIDEE TBM. The optimisation reduces GPP magnitude across all vegetation types except C4 plants. Global mean annual GPP therefore decreases from 194 ± 57 PgCyr −1 to 166 ± 10 PgCyr −1 , bringing the model more in line with an up-scaled flux tower estimate of 133 PgCyr −1. Strongest reductions in GPP are seen in boreal forests: the result is a shift in global GPP distribution, with a ~50% increase in the tropical to boreal productivity ratio. The optimisation resulted in a greater reduction in GPP than similar ORCHIDEE parameter optimisation studies using satellite-derived NDVI from MODIS and eddy covariance measurements of net CO 2 fluxes from the FLUXNET network. Our study shows that SIF data will be instrumental in constraining TBM GPP estimates, with a consequent improvement in global carbon cycle projections. The terrestrial carbon, C, sink remains the most uncertain component of the annual global carbon budget 1. Uncertainty in its strength and location contributes to high terrestrial biosphere model (TBM) spread in future C sink projections between models 2. Accurate net CO 2 flux projections rely on model ability to determine gross C fluxes. However, TBM inter-comparisons have shown strong discrepancies in gross C uptake (or gross primary production – GPP) related to both variability in growing season length and peak season magnitude 3,4. One source of uncertainty in TBM simulations is due to fixed (often uncertain) parameter values. Significant progress has been made in using carbon cycle-related observations to constrain TBM parametric uncertainty via Bayesian data assimilation (DA) methods 5–10. These datasets have included eddy covariance measurements of net ecosystem exchange (NEE) 11 , satellite-derived measures of vegetation dynamics 12–14 , and ground-based atmospheric CO 2 concentration data. However, while there is considerable improvement in the simulation of leaf phenology and/ or NEE in these studies, there is often a remaining model-data discrepancy in the gross C fluxes. Satellite-derived measures of sun-induced chlorophyll fluorescence (SIF) offer a promising new direction to constrain simulated GPP at multiple scales 15. SIF is strongly linked to GPP via its association with chlorophyll a absorption in plant photosynthetic machinery. The SIF-GPP relationship has been assessed at multiple scales using both process-based modelling and in situ and satellite observations. Frankenberg C. et al. 16 and Guanter L. et al. 17 were the first to report a linear relationship at global scale between monthly satellite-derived SIF data
The Salford Advanced Laser Canopy Analyser (SALCA): A multispectral full waveform LiDAR for improved vegetation characterisation
Vegetation canopy structure influences key physiological and ecological processes, such as photos... more Vegetation canopy structure influences key physiological and ecological processes, such as photosynthesis and net primary production. Accurate measurement of canopy parameters such as leaf area index and canopy cover via direct methods is time- consuming. Indirect methods are limited by an inability to distinguish woody material and foliage, assumptions relating to canopy leaf angle distribution and clumping and the lack
There is an increasing need to consistently combine observations from different sensors to monito... more There is an increasing need to consistently combine observations from different sensors to monitor the state of the land surface. In order to achieve this, robust methods based on the inversion of radiative transfer (RT) models can be used to interpret the satellite observations. This typically results in an inverse problem, but a major drawback of these methods is the computational complexity. We introduce the concept of Gaussian Process (GP) emulators: surrogate functions that accurately approximate RT models using a small set of input (e.g., leaf area index, leaf chlorophyll, etc.) and output (e.g., top-of-canopy reflectances or at sensor radiances) pairs. The emulators quantify the uncertainty of their approximation, and provide a fast and easy route to estimating the Jacobian of the original model, enabling the use of e.g., efficient gradient descent methods. We demonstrate the emulation of widely used RT models (PROSAIL and SEMIDISCRETE) and the coupling of vegetation and atmospheric (6S) RT models targetting particular sensor bands. A comparison with the full original model outputs shows that the emulators are a viable option to replace the original model, with negligible bias and discrepancies which are much smaller than the typical uncertainty in the observations. We also extend the theory of GP to cope with models with multivariate outputs (e.g., over the full solar reflective domain), and apply this to the emulation of PROSAIL, coupled 6S and PROSAIL and to the emulation of individual spectral components of 6S. In all cases, emulators successfully predict the full model output as well as accurately predict the gradient of the model calculated by finite differences, and produce speed ups between 10,000 and 50,000 times that of the original model. Finally, we use emulators to invert leaf area index (LAI), leaf chlorophyll content (C ab) and equivalent leaf water thickness (C w) from a time series of observations from Sentinel-2/MSI, Sentinel-3/SLSTR and Proba-V observations. We use sophisticated Hamiltonian Markov Chain Monte Carlo (MCMC) methods that exploit the speed of the emulators as well as the gradient estimation, a variational data assimilation (DA) method that extends the problem with temporal regularisation, and a particle filter using a regularisation model. The variational and particle filter approach appear more successful (meaning parameters closer to the truth, and smaller uncertainties) than the MCMC approach as a result of using the temporal regularisation mode. These work therefore suggests that GP emulators are a practical way to implement sophisticated parameter retrieval schemes in an era of increasing data volumes.
IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174), 1998
A fieldwork campaign was undertaken in East Anglia, UK (52" 37.2' N 0" 32.0' E), during the winte... more A fieldwork campaign was undertaken in East Anglia, UK (52" 37.2' N 0" 32.0' E), during the winter/spring growing season of 1997. Manual structural measurements were made of individual plants from a variety of crops in order to allow detailed geometric representations of these plants to be constructed within the Botanical Plant Modelling System (BPMS) [1] [2] with the aim of exploring and validating the extraction of canopy structural information from a variety of remotely sensed data. Results are presented from simulations carried out using BPMS data of barley crops at a variety of stages of growth. Measured directional reflectance data are compared with BPMS simulations, and derived structural parameters (LAI, %age cover) compared with independent measurements made in the field. Results show that the derived reflectance values are generally in good agreement with those obtained by direct measurement, whilst the %age cover and LAI values are more variable. This may be due to the difficulty of characterising inherently variable parameters with limited manual measurements.
Satellite monitoring of disturbances in Arctic ecosystems
International Geoscience and Remote Sensing Symposium (IGARSS), 2009
Abstract This study explores the capability of satellite remote sensing to detect relatively rapi... more Abstract This study explores the capability of satellite remote sensing to detect relatively rapid changes of vegetation cover in northern Fennoscandian regions in response to disturbance more generally, and insect defoliation damage in particular. The data used is a long term time series of leaf area index (LAI) at 8 Km resolution derived from the Advanced Very High Resolution Radiometer (AVHRR) between 1982 and 2006, developed to be structurally consistent with the Moderate Resolution Imaging Spectrometer (MODIS) ...
Global albedo, BRDF and nadir BRDF-adjusted reflectance products from MODIS
IEEE International Geoscience and Remote Sensing Symposium, 2002
Annual sequences of the first reprocessed albedo, bidirectional reflectance distribution function... more Annual sequences of the first reprocessed albedo, bidirectional reflectance distribution function (BRDF), and nadir BRDF-adjusted surface reflectance (NBAR) products are being evaluated. BRDF model parameters (or weights) are used to compute black sky albedo at local solar noon and white sky albedo and to compute surface reflectance at a common nadir geometry. In addition to these standard resolution albedo, BRDF,
A global data set of cloud occurrence probability derived from Moderate Resolution Imaging Spectr... more A global data set of cloud occurrence probability derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua gridded daily data is analyzed to investigate the probability of obtaining at least a minimum number of cloud-free observations within various compositing periods. The probabilities derived from Terra and Aqua, with morning and afternoon overpass times, respectively, are similar and increase with compositing period. Compositing both Terra and Aqua observations results in considerably higher probabilities of obtaining a sufficient number of observations for bidirectional reflectance model-based compositing. Given that the only alternative to obtaining sufficient samples is to extend the observation period, which can cause significant problems when the surface state changes, it is concluded that using data from the two MODIS sensors provides the most effective way of generating composited products. Findings with respect to the availability of cloud-free composites when n-day composites are generated on a temporally overlapping daily rolling basis, i.e., every day, rather than every n-days, are also discussed for regional and global applications.
On canopy spectral invariants and hyperspectral ray tracing
ABSTRACT In this paper we present a method for the efficient simulation of canopy hyperspectral r... more ABSTRACT In this paper we present a method for the efficient simulation of canopy hyperspectral reflectance using Monte Carlo Ray Tracing. The method essentially describes the scattered radiation in terms of spectral invariants that gives an expression as a series of powers of leaf single scattering albedo. This can then be post-processed to describe the scattering regime for arbitrary leaf spectral functions. The spectral invariant expression is explored to interpret some of its features. Some practical uses of this include the use of truncated ray tracing methods that can be adjusted for unsampled scattering orders by consideration of energy conservation.
Estimating land surface albedo in the HAPEX-Sahel experiment: model-based inversions using ASAS
Results are presented of spectral directional-hemispherical reflectance data derived from multi-l... more Results are presented of spectral directional-hemispherical reflectance data derived from multi-look angle airborne imagery over HAPEX-Sahel in 1992, along with the spatial distribution of BRDF parameters for a kernel-driven model. The results and techniques discussed are relevant to albedo derivation from data of this sort from both airborne and forthcoming satellite sensors
Biophysical parameter retrieval from forest and crop canopies in the optical and microwave domains using 3D models of canopy structure
... P. Saich, P. Lewis and MI Disney Centre for Terrestrial Carbon Dynamics Dept. ... The basis o... more ... P. Saich, P. Lewis and MI Disney Centre for Terrestrial Carbon Dynamics Dept. ... The basis of the technique is (i) a representation of the dynamic 3D structure of vegetation that can be used to drive (ii) numerical models of optical canopy reflectance (drat) and microwave ...
Comparison of Discrete Return and Waveform Airborne Lidar Derived Estimates of Fractional Cover in an Australian Savanna
ABSTRACT The advance of commercial airborne lidar systems from discrete-return to waveform record... more ABSTRACT The advance of commercial airborne lidar systems from discrete-return to waveform recording instruments has made repeatable estimates of biophysical variables from these different methods questionable. Using an experimental airborne waveform lidar dataset acquired in an Australian savanna, this study presents a method for the derivation of canopy/ground backscatter coefficients from waveform lidar and a comparison of discrete return and waveform approaches to the estimation of fractional cover. Despite limited validation, the results indicate that waveform estimates of fractional cover can provide consistently higher accuracy than discrete return estimates under varying survey properties. Ongoing work using raw waveform data across larger areas and 3D radiative transfer simulations aims to develop a quantitative understanding of the impact of disparate sensor and survey properties on the detection of change in vegetation structure using commercial lidar instruments.
The FLuorescence EXplorer (FLEX) mission proposes to launch a satellite for the global monitoring... more The FLuorescence EXplorer (FLEX) mission proposes to launch a satellite for the global monitoring of steady-state chlorophyll fluorescence in terrestrial vegetation. Fluorescence is a sensitive probe of photosynthetic function in both healthy and physiologically perturbed vegetation, and a powerful non-invasive tool to track the status, resilience, and recovery of photochemical processes and moreover provides important information on overall photosynthetic performance with implications for related carbon sequestration. The early responsiveness of fluorescence to atmospheric, soil and plant water balance, as well as to atmospheric chemistry and human intervention in land usage makes it an obvious biological indicator in improving our understanding of Earth system dynamics. The amenability of fluorescence to remote, even space-based observation qualifies it to join the emerging suite of space-based technologies for Earth observation. FLEX would encompass a three-instrument array for m...
The FLuorescence EXplorer (FLEX) mission proposes to launch a satellite for the global monitoring... more The FLuorescence EXplorer (FLEX) mission proposes to launch a satellite for the global monitoring of steady-state chlorophyll fluorescence in terrestrial vegetation. Fluorescence is a sensitive probe of photosynthetic function in both healthy and physiologically perturbed vegetation, and a powerful non-invasive tool to track the status, resilience, and recovery of photochemical processes and moreover provides important information on overall photosynthetic performance with implications for related carbon sequestration. The early responsiveness of fluorescence to atmospheric, soil and plant water balance, as well as to atmospheric chemistry and human intervention in land usage makes it an obvious biological indicator in improving our understanding of Earth system dynamics. The amenability of fluorescence to remote, even space-based observation qualifies it to join the emerging suite of space-based technologies for Earth observation. FLEX would encompass a three-instrument array for m...
Accurate terrestrial biosphere model (TBM) simulations of gross carbon uptake (gross primary prod... more Accurate terrestrial biosphere model (TBM) simulations of gross carbon uptake (gross primary productivity – GPP) are essential for reliable future terrestrial carbon sink projections. However, uncertainties in TBM GPP estimates remain. Newly-available satellite-derived sun-induced chlorophyll fluorescence (SIF) data offer a promising direction for addressing this issue by constraining regional-to-global scale modelled GPP. Here, we use monthly 0.5° GOME-2 SIF data from 2007 to 2011 to optimise GPP parameters of the ORCHIDEE TBM. The optimisation reduces GPP magnitude across all vegetation types except C4 plants. Global mean annual GPP therefore decreases from 194 ± 57 PgCyr −1 to 166 ± 10 PgCyr −1 , bringing the model more in line with an up-scaled flux tower estimate of 133 PgCyr −1. Strongest reductions in GPP are seen in boreal forests: the result is a shift in global GPP distribution, with a ~50% increase in the tropical to boreal productivity ratio. The optimisation resulted in a greater reduction in GPP than similar ORCHIDEE parameter optimisation studies using satellite-derived NDVI from MODIS and eddy covariance measurements of net CO 2 fluxes from the FLUXNET network. Our study shows that SIF data will be instrumental in constraining TBM GPP estimates, with a consequent improvement in global carbon cycle projections. The terrestrial carbon, C, sink remains the most uncertain component of the annual global carbon budget 1. Uncertainty in its strength and location contributes to high terrestrial biosphere model (TBM) spread in future C sink projections between models 2. Accurate net CO 2 flux projections rely on model ability to determine gross C fluxes. However, TBM inter-comparisons have shown strong discrepancies in gross C uptake (or gross primary production – GPP) related to both variability in growing season length and peak season magnitude 3,4. One source of uncertainty in TBM simulations is due to fixed (often uncertain) parameter values. Significant progress has been made in using carbon cycle-related observations to constrain TBM parametric uncertainty via Bayesian data assimilation (DA) methods 5–10. These datasets have included eddy covariance measurements of net ecosystem exchange (NEE) 11 , satellite-derived measures of vegetation dynamics 12–14 , and ground-based atmospheric CO 2 concentration data. However, while there is considerable improvement in the simulation of leaf phenology and/ or NEE in these studies, there is often a remaining model-data discrepancy in the gross C fluxes. Satellite-derived measures of sun-induced chlorophyll fluorescence (SIF) offer a promising new direction to constrain simulated GPP at multiple scales 15. SIF is strongly linked to GPP via its association with chlorophyll a absorption in plant photosynthetic machinery. The SIF-GPP relationship has been assessed at multiple scales using both process-based modelling and in situ and satellite observations. Frankenberg C. et al. 16 and Guanter L. et al. 17 were the first to report a linear relationship at global scale between monthly satellite-derived SIF data
The Salford Advanced Laser Canopy Analyser (SALCA): A multispectral full waveform LiDAR for improved vegetation characterisation
Vegetation canopy structure influences key physiological and ecological processes, such as photos... more Vegetation canopy structure influences key physiological and ecological processes, such as photosynthesis and net primary production. Accurate measurement of canopy parameters such as leaf area index and canopy cover via direct methods is time- consuming. Indirect methods are limited by an inability to distinguish woody material and foliage, assumptions relating to canopy leaf angle distribution and clumping and the lack
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Papers by Philip Lewis