Unmanned Aerial Systems (UAS)-Based Methods for Solar Induced Chlorophyll Fluorescence (SIF) Retrieval with Non-Imaging Spectrometers: State of the Art

Chlorophyll fluorescence (ChlF) information offers a deep insight into the plant physiological status by reason of the close relationship it has with the photosynthetic activity. The unmanned aerial systems (UAS)-based assessment of solar induced ChlF (SIF) using non-imaging spectrometers and radiance-based retrieval methods, has the potential to provide spatio-temporal photosynthetic performance information at field scale. The objective of this manuscript is to report the main advances in the development of UAS-based methods for SIF retrieval with non-imaging spectrometers through the latest scientific contributions, some of which are being developed within the frame of the Training on Remote Sensing for Ecosystem Modelling (TRuStEE) program. Investigations from the Universities of Edinburgh (School of Geosciences) and Tasmania (School of Technology, Environments and Design) are first presented, both sharing the principle of the spectroradiometer optical path bifurcation throughout, the so called ‘Piccolo-Doppio’ and ‘AirSIF’ systems, respectively. Furthermore, JB Hyperspectral Devices’ ongoing investigations towards the closest possible characterization of the atmospheric interference suffered by orbital platforms are outlined. The latest approach focuses on the observation of one single ground point across a multiple-kilometer atmosphere vertical column using the high altitude UAS named as AirFloX, mounted on a specifically designed and manufactured fixed wing platform: ‘FloXPlane’. We present technical details and preliminary results obtained from each instrument, a summary of their main characteristics, and finally the remaining challenges and open research questions are addressed. On the basis of the presented findings, the consensus is that SIF can be retrieved from low altitude spectroscopy. However, the UAS-based methods for SIF retrieval still present uncertainties associated with the current sensor characteristics and the spatio-temporal mismatching between aerial and ground measurements, which complicate robust validations. Complementary studies regarding the standardization of calibration methods and the characterization of spectroradiometers and data processing workflows are also required. Moreover, other open research questions such as those related to the implementation of atmospheric correction, bidirectional reflectance distribution function (BRDF) correction, and accurate surface elevation models remain to be addressed

New Methods for Measurements of Photosynthesis from Space

Our ability to close the Earth's carbon budget and predict feedbacks in a warming climate depends critically on knowing where, when, and how carbon dioxide (CO2) is exchanged between the land and atmosphere. In particular, determining the rate of carbon fixation by the Earth's biosphere (commonly referred to as gross primary productivity, or GPP) and the dependence of this productivity on climate is a central goal. Historically, GPP has been inferred from spectral imagery of the land and ocean. Assessment of GPP from the color of the land and ocean requires, however, additional knowledge of the types of plants in the scene, their regulatory mechanisms, and climate variables such as soil moisture—just the independent variables of interest! Sunlight absorbed by chlorophyll in photosynthetic organisms is mostly used to drive photosynthesis, but some can also be dissipated as heat or re‐radiated at longer wavelengths (660–800 nm). This near‐infrared light re‐emitted from illuminated plants is termed solarinduced fluorescence (SIF), and it has been found to strongly correlate with GPP. To advance our understanding of SIF and its relation to GPP and environmental stress at the planetary scale, the Keck Institute for Space Studies (KISS) convened a workshop—held in Pasadena, California, in August 2012—to focus on a newly developed capacity to monitor chlorophyll fluorescence from terrestrial vegetation by satellite. This revolutionary approach for retrieving global observations of SIF promises to provide direct and spatially resolved information on GPP, an ideal bottom‐up complement to the atmospheric net CO2 exchange inversions. Workshop participants leveraged our efforts on previous studies and workshops related to the European Space Agency’s FLuorescence EXplorer (FLEX) mission concept, which had already targeted SIF for a possible satellite mission and had developed a vibrant research community with many important publications. These studies, mostly focused on landscape, canopy, and leaf‐level interpretation, provided the ground‐work for the workshop, which focused on the global carbon cycle and synergies with atmospheric net flux inversions. Workshop participants included key members of several communities: plant physiologists with experience using active fluorescence methods to quantify photosynthesis; ecologists and radiative transfer experts who are studying the challenge of scaling from the leaf to regional scales; atmospheric scientists with experience retrieving photometric information from space‐borne spectrometers; and carbon cycle experts who are integrating new observations into models that describe the exchange of carbon between the atmosphere, land and ocean. Together, the participants examined the link between “passive” fluorescence observed from orbiting spacecraft and the underlying photochemistry, plant physiology and biogeochemistry of the land and ocean. This report details the opportunity for forging a deep connection between scientists doing basic research in photosynthetic mechanisms and the more applied community doing research on the Earth System. Too often these connections have gotten lost in empiricism associated with the coarse scale of global models. Chlorophyll fluorescence has been a major tool for basic research in photosynthesis for nearly a century. SIF observations from space, although sensing a large footprint, probe molecular events occurring in the leaves below. This offers an opportunity for direct mechanistic insight that is unparalleled for studies of biology in the Earth System. A major focus of the workshop was to review the basic mechanisms that underlie this phenomenon, and to explore modeling tools that have been developed to link the biophysical and biochemical knowledge of photosynthesis with the observable—in this case, the radiance of SIF—seen by the satellite. Discussions led to the identification of areas where knowledge is still lacking. For example, the inability to do controlled illumination observations from space limits the ability to fully constrain the variables that link fluorescence and photosynthesis. Another focus of the workshop explored a “top‐down” view of the SIF signal from space. Early studies clearly identified a strong correlation between the strength of this signal and our best estimate of the rate of photosynthesis (GPP) over the globe. New studies show that this observation provides improvements over conventional reflectance‐based remote sensing in detecting seasonal and environmental (particularly drought related) modulation of photosynthesis. Apparently SIF responds much more quickly and with greater dynamic range than typical greenness indices when GPP is perturbed. However, discussions at the workshop also identified areas where top‐down analysis seemed to be “out in front” of mechanistic studies. For example, changes in SIF based on changes in canopy light interception and the light use efficiency of the canopy, both of which occur in response to drought, are assumed equivalent in the top‐down analysis, but the mechanistic justification for this is still lacking from the bottom‐up side. Workshop participants considered implications of these mechanistic and empirical insights for large‐scale models of the carbon cycle and biogeochemistry, and also made progress toward incorporating SIF as a simulated output in land surface models used in global and regional‐scale analysis of the carbon cycle. Comparison of remotely sensed SIF with modelsimulated SIF may open new possibilities for model evaluation and data assimilation, perhaps leading to better modeling tools for analysis of the other retrieval from GOSAT satellite, atmospheric CO2 concentration. Participants also identified another application for SIF: a linkage to the physical climate system arising from the ability to better identify regional development of plant water stress. Decreases in transpiration over large areas of a continent are implicated in the development and “locking‐in” of drought conditions. These discussions also identified areas where current land surface models need to be improved in order to enable this research. Specifically, the radiation transport treatments need dramatic overhauls to correctly simulate SIF. Finally, workshop participants explored approaches for retrieval of SIF from satellite and ground‐based sensors. The difficulty of resolving SIF from the overwhelming flux of reflected sunlight in the spectral region where fluorescence occurs was once a major impediment to making this measurement. Placement of very high spectral resolution spectrometers on GOSAT (and other greenhouse gas–sensing satellites) has enabled retrievals based on infilling of solar Fraunhofer lines, enabling accurate fluorescence measurements even in the presence of moderately thick clouds. Perhaps the most interesting challenge here is that there is no readily portable ground‐based instrumentation that even approaches the capability of GOSAT and other planned greenhouse gas satellites. This strongly limits scientists’ ability to conduct ground‐based studies to characterize the footprint of the GOSAT measurement and to conduct studies of radiation transport needed to interpret SIF measurement. The workshop results represent a snapshot of the state of knowledge in this area. New research activities have sprung from the deliberations during the workshop, with publications to follow. The introduction of this new measurement technology to a wide slice of the community of Earth System Scientists will help them understand how this new technology could help solve problems in their research, address concerns about the interpretation, identify future research needs, and elicit support of the wider community for research needed to support this observation. Somewhat analogous to the original discovery that vegetation indices could be derived from satellite measurements originally intended to detect clouds, the GOSAT observations are a rare case in which a (fortuitous) global satellite dataset becomes available before the research community had a consolidated understanding on how (beyond an empirical correlation) it could be applied to understanding the underlying processes. Vegetation indices have since changed the way we see the global biosphere, and the workshop participants envision that fluorescence can perform the next indispensable step by complementing these measurements with independent estimates that are more indicative of actual (as opposed to potential) photosynthesis. Apart from the potential FLEX mission, no dedicated satellite missions are currently planned. OCO‐2 and ‐3 will provide much more data than GOSAT, but will still not allow for regional studies due to the lack of mapping capabilities. Geostationary observations may even prove most useful, as they could track fluorescence over the course of the day and clearly identify stress‐related down‐regulation of photosynthesis. Retrieval of fluorescence on the global scale should be recognized as a valuable tool; it can bring the same quantum leap in our understanding of the global carbon cycle as vegetation indices once did

Dynamics of sun-induced chlorophyll fluorescence and reflectance to detect stress-induced variations in canopy photosynthesis

Passive measurement of sun-induced chlorophyll fluorescence (F) represents the most promising tool to quantify changes in photosynthetic functioning on a large scale. However, the complex relationship between this signal and other photosynthesis-related processes restricts its interpretation under stress conditions. To address this issue, we conducted a field campaign by combining daily airborne and ground-based measurements of F (normalized to photosynthetically active radiation), reflectance and surface temperature and related the observed changes to stress-induced variations in photosynthesis. A lawn carpet was sprayed with different doses of the herbicide Dicuran. Canopy-level measurements of gross primary productivity indicated dosage-dependent inhibition of photosynthesis by the herbicide. Dosage-dependent changes in normalized F were also detected. After spraying, we first observed a rapid increase in normalized F and in the Photochemical Reflectance Index, possibly due to the blockage of electron transport by Dicuran and the resultant impairment of xanthophyll-mediated non-photochemical quenching. This initial increase was followed by a gradual decrease in both signals, which coincided with a decline in pigment-related reflectance indices. In parallel, we also detected a canopy temperature increase after the treatment. These results demonstrate the potential of using F coupled with relevant reflectance indices to estimate stress-induced changes in canopy photosynthesis

Early detection and quantification of verticillium wilt in olive using hyperspectral and thermal imagery over large areas

© 2015 by the authors. Automatic methods for an early detection of plant diseases (i.e., visible symptoms at early stages of disease development) using remote sensing are critical for precision crop protection. Verticillium wilt (VW) of olive caused by Verticillium dahliae can be controlled only if detected at early stages of development. Linear discriminant analysis (LDA) and support vector machine (SVM) classification methods were applied to classify V. dahliae severity using remote sensing at large scale. High-resolution thermal and hyperspectral imagery were acquired with a manned platform which flew a 3000-ha commercial olive area. LDA reached an overall accuracy of 59.0% and a κ of 0.487 while SVM obtained a higher overall accuracy, 79.2% with a similar κ, 0.495. However, LDA better classified trees at initial and low severity levels, reaching accuracies of 71.4 and 75.0%, respectively, in comparison with the 14.3% and 40.6% obtained by SVM. Normalized canopy temperature, chlorophyll fluorescence, structural, xanthophyll, chlorophyll, carotenoid and disease indices were found to be the best indicators for early and advanced stage infection by VW. These results demonstrate that the methods developed in other studies at orchard scale are valid for flights in large areas comprising several olive orchards differing in soil and crop management characteristics.Financial support for this research was provided by Project P08-AGR-03528 from “Consejería de Economía, Innovación y Ciencia” of Junta de Andalucía and the European Social Fund, and projects AGL-2012-37521 and AGL2012-40053-C03-01 from the Spanish “Ministerio de Economía y Competitividad” and the European Social Fund. Rocio Calderón is a recipient of research fellowship BES-2010-035511 from the Spanish “Ministerio de Ciencia e Innovación”.We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).Peer Reviewe

Quantitative estimation of vegetation traits and temporal dynamics using 3-D radiative transfer models, high-resolution hyperspectral images and satellite imagery

Large-scale monitoring of vegetation dynamics by remote sensing is key to detecting early signs of vegetation decline. Spectral-based indicators of phys-iological plant traits (PTs) have the potential to quantify variations in pho-tosynthetic pigments, chlorophyll fluorescence emission, and structural changes of vegetation as a function of stress. However, the specific response of PTs to disease-induced decline in heterogeneous canopies remains largely unknown, which is critical for the early detection of irreversible damage at different scales. Four specific objectives were defined in this research: i) to assess the feasibility of modelling the incidence and severity of Phytophthora cinnamomi and Xylella fastidiosa based on PTs and biophysical properties of vegetation; ii) to assess non-visual early indicators, iii) to retrieve PT using radiative transfer models (RTM), high-resolution imagery and satellite observations; and iv) to establish the basis for scaling up PTs at different spatial resolutions using RTM for their retrieval in different vegetation co-vers. This thesis integrates different approaches combining field data, air- and space-borne imagery, and physical and empirical models that allow the retrieval of indicators and the evaluation of each component’s contribution to understanding temporal variations of disease-induced symptoms in heter-ogeneous canopies. Furthermore, the effects associated with the understory are introduced, showing not only their impact but also providing a compre-hensive model to account for it. Consequently, a new methodology has been established to detect vegetation health processes and the influence of biotic and abiotic factors, considering different components of the canopy and their impact on the aggregated signal. It is expected that, using the presented methods, existing remote sensors and future developments, the ability to detect and assess vegetation health globally will have a substantial impact not only on socio-economic factors, but also on the preservation of our eco-system as a whole

Evaluating solar-induced fluorescence across spatial and temporal scales to monitor primary productivity

Solar-induced chlorophyll fluorescence (SIF) has been widely cited in carbon cycling studies as a proxy for photosynthesis, and SIF data are commonly incorporated into terrestrial primary productivity models. Though satellite-based SIF products show close relationships with gross primary productivity (GPP), this is not universally true at intermediate scales. A meta-analysis of the tower-based and airborne SIF literature revealed that mean SIF retrievals from unstressed vegetation span three orders of magnitude. While reporting on spectrometer calibration procedures, hardware characterizations, and associated corrections is inconsistent, laboratory and field experiments show that these factors may contribute to significant uncertainty in SIF retrievals. Additionally, there remain ongoing questions regarding the interpretation of SIF data made across spatial scales and the link between satellite SIF retrievals and primary productivity on the ground. Chlorophyll fluorescence originates from dynamic energy partitioning at the leaf level and does not exhibit a uniformly linear relationship with photosynthesis at finer scales. As a standalone metric, SIF measured at the tower scale was not found to track changes in carbon assimilation following stomatal closure induced in deciduous woody tree branches. This lack of relationship may be explained by alternative energy partitioning pathways, such as thermal energy dissipation mediated by xanthophyll cycle pigments; the activity of these pigments can be tracked using the photochemical reflectance index (PRI). Gradual, phenological changes in energy partitioning are observed as changes in the slope of the SIF-PRI relationship over the course of a season. Along with high frequency effects such as wind-mediated changes in leaf orientation and reflectance, and rapid changes in sky condition due to clouds, PRI offers crucial insights needed to link SIF to leaf physiology. While SIF offers tremendous promise for improving the characterization of terrestrial carbon exchange, and a fuller understanding of the boundaries on its utility and interpretation as a biophysical phenomenon will help to create more reliable models of global productivity

New Methods for Measurements of Photosynthesis from Space

Our ability to close the Earth's carbon budget and predict feedbacks in a warming climate depends critically on knowing where, when, and how carbon dioxide (CO2) is exchanged between the land and atmosphere. In particular, determining the rate of carbon fixation by the Earth's biosphere (commonly referred to as gross primary productivity, or GPP) and the dependence of this productivity on climate is a central goal. Historically, GPP has been inferred from spectral imagery of the land and ocean. Assessment of GPP from the color of the land and ocean requires, however, additional knowledge of the types of plants in the scene, their regulatory mechanisms, and climate variables such as soil moisture—just the independent variables of interest! Sunlight absorbed by chlorophyll in photosynthetic organisms is mostly used to drive photosynthesis, but some can also be dissipated as heat or re‐radiated at longer wavelengths (660–800 nm). This near‐infrared light re‐emitted from illuminated plants is termed solarinduced fluorescence (SIF), and it has been found to strongly correlate with GPP. To advance our understanding of SIF and its relation to GPP and environmental stress at the planetary scale, the Keck Institute for Space Studies (KISS) convened a workshop—held in Pasadena, California, in August 2012—to focus on a newly developed capacity to monitor chlorophyll fluorescence from terrestrial vegetation by satellite. This revolutionary approach for retrieving global observations of SIF promises to provide direct and spatially resolved information on GPP, an ideal bottom‐up complement to the atmospheric net CO2 exchange inversions. Workshop participants leveraged our efforts on previous studies and workshops related to the European Space Agency’s FLuorescence EXplorer (FLEX) mission concept, which had already targeted SIF for a possible satellite mission and had developed a vibrant research community with many important publications. These studies, mostly focused on landscape, canopy, and leaf‐level interpretation, provided the ground‐work for the workshop, which focused on the global carbon cycle and synergies with atmospheric net flux inversions. Workshop participants included key members of several communities: plant physiologists with experience using active fluorescence methods to quantify photosynthesis; ecologists and radiative transfer experts who are studying the challenge of scaling from the leaf to regional scales; atmospheric scientists with experience retrieving photometric information from space‐borne spectrometers; and carbon cycle experts who are integrating new observations into models that describe the exchange of carbon between the atmosphere, land and ocean. Together, the participants examined the link between “passive” fluorescence observed from orbiting spacecraft and the underlying photochemistry, plant physiology and biogeochemistry of the land and ocean. This report details the opportunity for forging a deep connection between scientists doing basic research in photosynthetic mechanisms and the more applied community doing research on the Earth System. Too often these connections have gotten lost in empiricism associated with the coarse scale of global models. Chlorophyll fluorescence has been a major tool for basic research in photosynthesis for nearly a century. SIF observations from space, although sensing a large footprint, probe molecular events occurring in the leaves below. This offers an opportunity for direct mechanistic insight that is unparalleled for studies of biology in the Earth System. A major focus of the workshop was to review the basic mechanisms that underlie this phenomenon, and to explore modeling tools that have been developed to link the biophysical and biochemical knowledge of photosynthesis with the observable—in this case, the radiance of SIF—seen by the satellite. Discussions led to the identification of areas where knowledge is still lacking. For example, the inability to do controlled illumination observations from space limits the ability to fully constrain the variables that link fluorescence and photosynthesis. Another focus of the workshop explored a “top‐down” view of the SIF signal from space. Early studies clearly identified a strong correlation between the strength of this signal and our best estimate of the rate of photosynthesis (GPP) over the globe. New studies show that this observation provides improvements over conventional reflectance‐based remote sensing in detecting seasonal and environmental (particularly drought related) modulation of photosynthesis. Apparently SIF responds much more quickly and with greater dynamic range than typical greenness indices when GPP is perturbed. However, discussions at the workshop also identified areas where top‐down analysis seemed to be “out in front” of mechanistic studies. For example, changes in SIF based on changes in canopy light interception and the light use efficiency of the canopy, both of which occur in response to drought, are assumed equivalent in the top‐down analysis, but the mechanistic justification for this is still lacking from the bottom‐up side. Workshop participants considered implications of these mechanistic and empirical insights for large‐scale models of the carbon cycle and biogeochemistry, and also made progress toward incorporating SIF as a simulated output in land surface models used in global and regional‐scale analysis of the carbon cycle. Comparison of remotely sensed SIF with modelsimulated SIF may open new possibilities for model evaluation and data assimilation, perhaps leading to better modeling tools for analysis of the other retrieval from GOSAT satellite, atmospheric CO2 concentration. Participants also identified another application for SIF: a linkage to the physical climate system arising from the ability to better identify regional development of plant water stress. Decreases in transpiration over large areas of a continent are implicated in the development and “locking‐in” of drought conditions. These discussions also identified areas where current land surface models need to be improved in order to enable this research. Specifically, the radiation transport treatments need dramatic overhauls to correctly simulate SIF. Finally, workshop participants explored approaches for retrieval of SIF from satellite and ground‐based sensors. The difficulty of resolving SIF from the overwhelming flux of reflected sunlight in the spectral region where fluorescence occurs was once a major impediment to making this measurement. Placement of very high spectral resolution spectrometers on GOSAT (and other greenhouse gas–sensing satellites) has enabled retrievals based on infilling of solar Fraunhofer lines, enabling accurate fluorescence measurements even in the presence of moderately thick clouds. Perhaps the most interesting challenge here is that there is no readily portable ground‐based instrumentation that even approaches the capability of GOSAT and other planned greenhouse gas satellites. This strongly limits scientists’ ability to conduct ground‐based studies to characterize the footprint of the GOSAT measurement and to conduct studies of radiation transport needed to interpret SIF measurement. The workshop results represent a snapshot of the state of knowledge in this area. New research activities have sprung from the deliberations during the workshop, with publications to follow. The introduction of this new measurement technology to a wide slice of the community of Earth System Scientists will help them understand how this new technology could help solve problems in their research, address concerns about the interpretation, identify future research needs, and elicit support of the wider community for research needed to support this observation. Somewhat analogous to the original discovery that vegetation indices could be derived from satellite measurements originally intended to detect clouds, the GOSAT observations are a rare case in which a (fortuitous) global satellite dataset becomes available before the research community had a consolidated understanding on how (beyond an empirical correlation) it could be applied to understanding the underlying processes. Vegetation indices have since changed the way we see the global biosphere, and the workshop participants envision that fluorescence can perform the next indispensable step by complementing these measurements with independent estimates that are more indicative of actual (as opposed to potential) photosynthesis. Apart from the potential FLEX mission, no dedicated satellite missions are currently planned. OCO‐2 and ‐3 will provide much more data than GOSAT, but will still not allow for regional studies due to the lack of mapping capabilities. Geostationary observations may even prove most useful, as they could track fluorescence over the course of the day and clearly identify stress‐related down‐regulation of photosynthesis. Retrieval of fluorescence on the global scale should be recognized as a valuable tool; it can bring the same quantum leap in our understanding of the global carbon cycle as vegetation indices once did

Detection of Xylella fastidiosa in almond orchards by synergic use of an epidemic spread model and remotely sensed plant traits

The early detection of Xylella fastidiosa (Xf) infections is critical to the management of this dangerous plan pathogen across the world. Recent studies with remote sensing (RS) sensors at different scales have shown that Xf-infected olive trees have distinct spectral features in the visible and infrared regions (VNIR). However, further work is needed to integrate remote sensing in the management of plant disease epidemics. Here, we research how the spectral changes picked up by different sets of RS plant traits (i.e., pigments, structural or leaf protein content), can help capture the spatial dynamics of Xf spread. We coupled a spatial spread model with the probability of Xf-infection predicted by a RS-driven support vector machine (RS-SVM) model. Furthermore, we analyzed which RS plant traits contribute most to the output of the prediction models. For that, in almond orchards affected by Xf (n = 1426 trees), we conducted a field campaign simultaneously with an airborne campaign to collect high-resolution thermal images and hyperspectral images in the visible-near-infrared (VNIR, 400–850 nm) and short-wave infrared regions (SWIR, 950–1700 nm). The best performing RS-SVM model (OA = 75%; kappa = 0.50) included as predictors leaf protein content, nitrogen indices (NIs), fluorescence and a thermal indicator (Tc), alongside pigments and structural parameters. Leaf protein content together with NIs contributed 28% to the explanatory power of the model, followed by chlorophyll (22%), structural parameters (LAI and LIDFa), and chlorophyll indicators of photosynthetic efficiency. Coupling the RS model with an epidemic spread model increased the accuracy (OA = 80%; kappa = 0.48). In the almond trees where the presence of Xf was assayed by qPCR (n = 318 trees), the combined RS-spread model yielded an OA of 71% and kappa = 0.33, which is higher than the RS-only model and visual inspections (both OA = 64–65% and kappa = 0.26–31). Our work demonstrates how combining spatial epidemiological models and remote sensing can lead to highly accurate predictions of plant disease spatial distribution