Caroline J. Nichol
University of Edinburgh
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Featured researches published by Caroline J. Nichol.
Agricultural and Forest Meteorology | 2000
Caroline J. Nichol; Karl Fred Huemmrich; T. Andrew Black; P. G. Jarvis; Charles L. Walthall; John Grace; Forrest G. Hall
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.
Oecologia | 2012
Albert Porcar-Castell; José Ignacio García-Plazaola; Caroline J. Nichol; Pasi Kolari; Beñat Olascoaga; Nea Kuusinen; Beatriz Fernández-Marín; Minna Pulkkinen; Eero Nikinmaa
The photochemical reflectance index (PRI) is regarded as a promising proxy to track the dynamics of photosynthetic light use efficiency (LUE) via remote sensing. The implementation of this approach requires the relationship between PRI and LUE to scale not only in space but also in time. The short-term relationship between PRI and LUE is well known and is based on the regulative process of non-photochemical quenching (NPQ), but at the seasonal timescale the mechanisms behind the relationship remain unclear. We examined to what extent sustained forms of NPQ, photoinhibition of reaction centres, seasonal changes in leaf pigment concentrations, or adjustments in the capacity of alternative energy sinks affect the seasonal relationship between PRI and LUE during the year in needles of boreal Scots pine. PRI and NPQ were highly correlated during most of the year but decoupled in early spring when the foliage was deeply downregulated. This phenomenon was attributed to differences in the physiological mechanisms controlling the seasonal dynamics of PRI and NPQ. Seasonal adjustments in the pool size of the xanthophyll cycle pigments, on a chlorophyll basis, controlled the dynamics of PRI, whereas the xanthophyll de-epoxidation status and other xanthophyll-independent mechanisms controlled the dynamics of NPQ at the seasonal timescale. We conclude that the PRI leads to an underestimation of NPQ, and consequently overestimation of LUE, under conditions of severe stress in overwintering Scots pine, and most likely also in species experiencing severe drought. This severe stress-induced decoupling may challenge the implementation of the PRI approach.
Sensors | 2011
Manuela Balzarolo; Karen Anderson; Caroline J. Nichol; Micol Rossini; L. Vescovo; Nicola Arriga; Georg Wohlfahrt; Jean-Christophe Calvet; Arnaud Carrara; Sofia Cerasoli; Sergio Cogliati; Fabrice Daumard; Lars Eklundh; J.A. Elbers; Fatih Evrendilek; R.N. Handcock; Jörg Kaduk; Katja Klumpp; Bernard Longdoz; Giorgio Matteucci; Michele Meroni; Leonardo Montagnani; Jean-Marc Ourcival; Enrique P. Sánchez-Cañete; Jean-Yves Pontailler; Radosław Juszczak; Bob Scholes; M. Pilar Martín
This paper reviews the currently available optical sensors, their limitations and opportunities for deployment at Eddy Covariance (EC) sites in Europe. This review is based on the results obtained from an online survey designed and disseminated by the Co-cooperation in Science and Technology (COST) Action ESO903—“Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe” that provided a complete view on spectral sampling activities carried out within the different research teams in European countries. The results have highlighted that a wide variety of optical sensors are in use at flux sites across Europe, and responses further demonstrated that users were not always fully aware of the key issues underpinning repeatability and the reproducibility of their spectral measurements. The key findings of this survey point towards the need for greater awareness of the need for standardisation and development of a common protocol of optical sampling at the European EC sites.
IEEE Geoscience and Remote Sensing Letters | 2011
Iain H. Woodhouse; Caroline J. Nichol; Peter Sinclair; Jim Jack; Felix Morsdorf; Tim J. Malthus; Genevieve Patenaude
The first demonstration of a multispectral light detection and ranging (LiDAR) optimized for detailed structure and physiology measurements in forest ecosystems is described. The basic principle is to utilize, in a single instrument, both the capacity of multispectral sensing to measure plant physiology [through normalized difference vegetation index (NDVI) and photochemical reflectance index (PRI)] with the ability of LiDAR to measure vertical structure information and generate “hot spot” (specular) reflectance data independent of solar illumination. A tunable laser operated at four wavelengths (531, 550, 660, and 780 nm) was used to measure profiles of the NDVI and the PRI. Laboratory-based measurements were conducted for live trees, demonstrating that realistic values of the indexes can be measured. A model-based analysis demonstrates that the LiDAR waveforms cannot only capture the tree height information but also picks up the seasonal and vertical variation of NDVI inside the tree canopy.
Remote Sensing | 2012
Andrew M. Wallace; Caroline J. Nichol; Iain H. Woodhouse
We describe the use of Bayesian inference techniques, notably Markov chain Monte Carlo (MCMC) and reversible jump MCMC (RJMCMC) methods, to recover forest structural and biochemical parameters from multispectral LiDAR (Light Detection and Ranging) data. We use a variable dimension, multi-layered model to represent a forest canopy or tree, and discuss the recovery of structure and depth profiles that relate to photochemical properties. We first demonstrate how simple vegetation indices such as the Normalized Differential Vegetation Index (NDVI), which relates to canopy biomass and light absorption, and Photochemical Reflectance Index (PRI) which is a measure of vegetation light use efficiency, can be measured from multispectral data. We further describe and demonstrate our layered approach on single wavelength real data, and on simulated multispectral data derived from real, rather than simulated, data sets. This evaluation shows successful recovery of a subset of parameters, as the complete recovery problem is ill-posed with the available data. We conclude that the approach has promise, and suggest future developments to address the current difficulties in parameter inversion.
Photogrammetric Engineering and Remote Sensing | 2007
Uwe Rascher; Caroline J. Nichol; Christopher Small; Leif Hendricks
Photosynthetic efficiency of higher plants dynamically adapts to changing light intensity and is greatly influenced by stress, such as water stress. We tested a new portable hyperspectral imaging system, the SOC-700, manufactured by Surface Optics, which produces 12-bit reflectance images between 440 nm and 880 nm with a 4 nm spectral resolution. We quantified the reflectance properties and photochemical reflectance index (PRI) during light adaptation of genetically modified Arabidopsis thaliana (L.) Heynh. plants lacking or over-expressing the PsbS protein, an essential component of the mechanism of non-photochemical dissipation. In a second experiment, PRI images of gradually water stressed leaves were compared to leaf-level measurements of reflectance using a second commercially available spectrometer, and chlorophyll fluorescence to detect dynamic, photosynthesis correlated changes in reflectance and PRI. In both experiments PRI measured with the SOC-700 changed, reflecting the biochemical adaptation of the photosynthetic apparatus to high light intensity (dynamic changes within minutes) and the gradual deactivation of photosynthesis during drying (changes within hours). The quantum efficiency of photosystem II (� F/Fm� ) and non-photochemical energy dissipation (NPQ) measured from chlorophyll fluorescence, were strongly correlated with PRI. Leaf area PRI values estimated from individual pixel spectra of the SOC-700 quantified photosynthetic efficiency more thoroughly than PRI values calculated from point measurements using the hand-held GER-1500. The applications, limitations, and potential of the SOC-700 for plant eco-physiology and remote sensing are also discussed.
Journal of Geophysical Research | 2011
Thomas Hilker; Forrest G. Hall; Caroline J. Nichol; Alexei Lyapustin; T. Andrew Black; Michael A. Wulder; Ray Leuning; Alan G. Barr; David Y. Hollinger; Bill Munger; Compton J. Tucker
[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.
IEEE Transactions on Geoscience and Remote Sensing | 2014
Andrew M. Wallace; Aongus McCarthy; Caroline J. Nichol; Ximing Ren; Simone Morak; Daniel Martinez-Ramirez; Iain H. Woodhouse; Gerald S. Buller
Multispectral light detection and ranging (LiDAR) has the potential to recover structural and physiological data from arboreal samples and, by extension, from forest canopies when deployed on aerial or space platforms. In this paper, we describe the design and evaluation of a prototype multispectral LiDAR system and demonstrate the measurement of leaf and bark area and abundance profiles using a series of experiments on tree samples “viewed from above” by tilting living conifers such that the apex is directed on the viewing axis. As the complete recovery of all structural and physiological parameters is ill posed with a restricted set of four wavelengths, we used leaf and bark spectra measured in the laboratory to constrain parameter inversion by an extended reversible jump Markov chain Monte Carlo algorithm. However, we also show in a separate experiment how the multispectral LiDAR can recover directly a profile of Normalized Difference Vegetation Index (NDVI), which is verified against the laboratory spectral measurements. Our work shows the potential of multispectral LiDAR to recover both structural and physiological data and also highlights the fine spatial resolution that can be achieved with time-correlated single-photon counting.
Journal of remote sensing | 2014
Guillaume G. Drolet; T. J. Wade; Caroline J. Nichol; Christopher MacLellan; Janne Levula; Albert Porcar-Castell; Eero Nikinmaa; Timo Vesala
This paper describes the development of a fully automated system for collecting high-resolution spectral data over a forested footprint. The system comprises a pair of off-the-shelf spectrometers in a custom-built thermal enclosure with a fixed off-nadir downward (target)-pointing fibre and upward-pointing fibre for irradiance measurement. Both instruments sample simultaneously via custom-written and user-controlled software during all weathers and sky conditions. The system is mounted on a 25 m eddy covariance scaffolding tower, approximately 7 m from a Scots pine forest canopy. The system was installed at the University of Helsinki’s SMEAR-II Field Station in Hyytiälä in March 2010 and has been operating continuously through a joint programme between the Universities of Edinburgh and Helsinki. The system was designed to capture diurnal and seasonal variation in vegetation light-use efficiency and fluorescence through the capture and analysis of well-defined narrow spectral features, but its implementation would permit the extraction of further optical signals linked to vegetation biophysical variables, and provide a continuous data stream with which to validate satellite data products including vegetation indices such as the photochemical reflectance index (PRI) as well as spectral indicators of solar induced fluorescence.
Journal of remote sensing | 2010
Caroline J. Nichol; John Grace
Leaf pigment concentrations are indicative of a range of plant physiological properties and processes. The measurement of leaf spectral reflectance is a rapid, non-destructive method for determining pigment content, and a large number of spectral indices have been developed for the estimation of leaf pigment content. Despite their ‘applicability’ across many species types, some ecologically important species remain to be explored. The objective of this paper was to investigate a wide range of hyperspectral indices for determining the chlorophyll and carotenoid content in a microphyllous and sclerophyllous species, Calluna vulgaris. We carried out spectral measurements on individual heather shoots with a handheld GER-1500 spectroradiometer, and sampled each measured shoot for biochemical analysis using high-performance liquid chromatography (HPLC). We found that several previously published indices performed relatively poorly and yielded coefficients of determination (R2) for chlorophyll ranging from 0.34 to 0.66, with the first derivative of reflectance at the red edge yielding the highest correlation with chlorophyll content (R2 = 0.66). Only one of the carotenoid indices we tested (the Photochemical Reflectance Index, PRI) provided a strong correlation with the de-epoxidation state of the xanthophyll cycle (R2 = 0.78). The other previously published carotenoid indices performed poorly within our data set. We concluded that only a few of the so-called ‘widely applicable’ indices were applicable to use with this data set, which would present limitations when working with remotely sensed data at a larger scale where a mix of species, including Calluna vulgaris, is present.
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Commonwealth Scientific and Industrial Research Organisation
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