Automated proximal sensing for estimation of the bidirectional reflectance distribution function in a Mediterranean tree-grass ecosystem

Premio Extraordinario de Doctorado de la UAH en el año académico 2015-2016Los sistemas automáticos de proximal sensing permiten adquirir información espectral de las cubiertas terrestres elevada frecuencia temporal, que puede relacionarse con observaciones remotas o de otros tipos de sensores como los sistemas de eddy covariance. Si bien inicialmente los sistemas automáticos empleaban sensores multi-banda, en los últimos años se ha incrementado el uso de sensores hiperespectrales. Si bien estos sensores ofrecen información redundante y de alta resolución espectral, las mediciones están sujetas a múltiples fuentes de incertidumbre; tanto instrumentales (dependencias de la temperatura o el nivel de señal) como direccionales (dependencia de la geometría de observación e iluminación). Las dependencias instrumentales pueden ser minimizadas, por ejemplo, controlando la temperatura del instrumento o el nivel de señal registrado. En otros casos, es necesario parametrizar y emplear modelos para corregir los datos. En la presente tesis doctoral los capítulos 1 al 3 presentan la caracterización completa de un espectrómetro de campo instalado en un sistema automático. Los capítulos 1 y 2 analizan las fuentes de no linealidad en este instrumento, una de las cuales no había sido anteriormente descrita en este tipo de instrumentos. El tercer capítulo muestra el conjunto completo de modelos de corrección de los efectos instrumentales y la cadena de procesado correspondiente. Por otro lado, los sistemas automáticos se enfrentan a efectos direccionales ya que adquieren mediciones continuamente durante el ciclo solar diario y bajo cualquier condición de iluminación. Esto maximiza los rangos de los ángulos de iluminación y también de la fracción difusa de la irradiancia. Esta variabilidad de condiciones de iluminación, combinada con una variación de los ángulos de observación permite obtener la información necesaria para caracterizar las respuestas direccionales de la cubierta observada. Algunos sistemas automáticos multi-angulares ya han sido empleados para realizar esta caracterización mediante la estimación de la Función de Distribución de Reflectividad Bidireccional (BRDF) en ecosistemas homogéneos. Sin embargo, esto no se ha conseguido aún en áreas heterogéneas, como es el caso de los ecosistemas tree-grass o de sabana. Así mismo, los trabajos previos no han considerado los efectos de la radiación difusa en el estudio del BRDF. En el capítulo 4 proponemos una metodología que permite desmezclar y caracterizar simultáneamente la función de distribución de reflectividad hemisférica-direccional de las dos cubiertas de vegetación presentes en el ecosistema, pasto y arbolado. También se analizan los efectos de las diferentes características del método. Finalmente, los resultados se escalan y se comparan con productos globales de satélite como el producto BRDF de MODIS. La conclusión obtenida es que se requieren más esfuerzos en el desarrollo y caracterización de sensores hiperespectrales instalados en sistemas automáticos de campo. Estos sistemas deberían adoptar configuraciones multi-angulares de modo que puedan caracterizarse las respuestas direccionales. Para ello, será necesario considerar los efectos de la radiación difusa; y en algunos casos también la heterogeneidad de la escena

Automated proximal sensing for estimation of the bidirectional reflectance distribution function in a Mediterranean tree-grass ecosystem

Premio Extraordinario de Doctorado de la UAH en el año académico 2015-2016Los sistemas automáticos de proximal sensing permiten adquirir información espectral de las cubiertas terrestres elevada frecuencia temporal, que puede relacionarse con observaciones remotas o de otros tipos de sensores como los sistemas de eddy covariance. Si bien inicialmente los sistemas automáticos empleaban sensores multi-banda, en los últimos años se ha incrementado el uso de sensores hiperespectrales. Si bien estos sensores ofrecen información redundante y de alta resolución espectral, las mediciones están sujetas a múltiples fuentes de incertidumbre; tanto instrumentales (dependencias de la temperatura o el nivel de señal) como direccionales (dependencia de la geometría de observación e iluminación). Las dependencias instrumentales pueden ser minimizadas, por ejemplo, controlando la temperatura del instrumento o el nivel de señal registrado. En otros casos, es necesario parametrizar y emplear modelos para corregir los datos. En la presente tesis doctoral los capítulos 1 al 3 presentan la caracterización completa de un espectrómetro de campo instalado en un sistema automático. Los capítulos 1 y 2 analizan las fuentes de no linealidad en este instrumento, una de las cuales no había sido anteriormente descrita en este tipo de instrumentos. El tercer capítulo muestra el conjunto completo de modelos de corrección de los efectos instrumentales y la cadena de procesado correspondiente. Por otro lado, los sistemas automáticos se enfrentan a efectos direccionales ya que adquieren mediciones continuamente durante el ciclo solar diario y bajo cualquier condición de iluminación. Esto maximiza los rangos de los ángulos de iluminación y también de la fracción difusa de la irradiancia. Esta variabilidad de condiciones de iluminación, combinada con una variación de los ángulos de observación permite obtener la información necesaria para caracterizar las respuestas direccionales de la cubierta observada. Algunos sistemas automáticos multi-angulares ya han sido empleados para realizar esta caracterización mediante la estimación de la Función de Distribución de Reflectividad Bidireccional (BRDF) en ecosistemas homogéneos. Sin embargo, esto no se ha conseguido aún en áreas heterogéneas, como es el caso de los ecosistemas tree-grass o de sabana. Así mismo, los trabajos previos no han considerado los efectos de la radiación difusa en el estudio del BRDF. En el capítulo 4 proponemos una metodología que permite desmezclar y caracterizar simultáneamente la función de distribución de reflectividad hemisférica-direccional de las dos cubiertas de vegetación presentes en el ecosistema, pasto y arbolado. También se analizan los efectos de las diferentes características del método. Finalmente, los resultados se escalan y se comparan con productos globales de satélite como el producto BRDF de MODIS. La conclusión obtenida es que se requieren más esfuerzos en el desarrollo y caracterización de sensores hiperespectrales instalados en sistemas automáticos de campo. Estos sistemas deberían adoptar configuraciones multi-angulares de modo que puedan caracterizarse las respuestas direccionales. Para ello, será necesario considerar los efectos de la radiación difusa; y en algunos casos también la heterogeneidad de la escena

Modelling, Monitoring and Validation of Plant Phenology Products

Phänologie, die Lehre der periodisch wiederkehrenden Entwicklungserscheinungen in der Natur, hat sich in den letzten Jahrzehnten zu einem wichtigen Teilgebiet der Klimaforschung entwickelt. Einer der Haupteffekte der globalen Erwärmung ist die Veränderung der Wachstumsmuster und Fortpflanzungsgewohnheiten von Pflanzen, und somit veränderte Phänologie. Um die Auswirkungen der Klimaveränderung auf wildwachsende sowie Kulturpflanzen vorherzusagen, werden phänologische Modelle angewendet, verbessert und validiert. Dabei ist Wissen über den aktuellen Stand der Vegetation notwendig, welches aus Beobachtungen und fernerkundliche Messungen gewonnen wird. Die hier präsentierte Arbeit befasst sich mit dem Verständnis der Zusammenhänge zwischen fernerkundlichen Messungen und phänologischen Stadien und somit den Herausforderungen der modernen phänologischen Forschung: Der Vorhersage der Phänologie durch Modellierungsansätze, der Beobachtung der Phänologie mit optischen boden- und satellitengestützten Sensoren und der Validierung phänologischer Produkte.Phenology, the study of recurring life cycle events of plants and animals has emerged as an important part of climate change research within the last decades. One of the main effects of global warming on vegetation is altered phenology, since plants have to modify their growth patterns and reproduction habits as reaction to changing environmental conditions. Forecasting phenology, thus phenological modelling, is a timely challenge given the necessity to predict the impact of global warming on wild-growing species and agricultural crops. However, assessing the present state of vegetation, thus phenological monitoring, is essential to update and validate model results. An improved comprehension of the relationships between plant phenology and remotely sensed products is crucial to interpret these results. Consequently, the presented thesis deals with the main challenges faced in modern phenology research, covering phenological forecasting with a modelling approach, satellite-based phenology extraction, and near-surface long-term monitoring of phenology

EUROSPEC : at the interface between remote-sensing and ecosystem CO2 flux measurements in Europe

Resolving the spatial and temporal dynamics of gross primary productivity (GPP) of terrestrial ecosystems across different scales remains a challenge. Remote sensing is regarded as the solution to upscale point observations conducted at the ecosystem level, using the eddy covariance (EC) technique, to the landscape and global levels. In addition to traditional vegetation indices, the photochemical reflectance index (PRI) and the emission of solar-induced chlorophyll fluorescence (SIF), now measurable from space, provide a new range of opportunities to monitor the global carbon cycle using remote sensing. However, the scale mismatch between EC observations and the much coarser satellite-derived data complicate the integration of the two sources of data. The solution is to establish a network of in situ spectral measurements that can act as a bridge between EC measurements and remote-sensing data. In situ spectral measurements have already been conducted for many years at EC sites, but using variable instrumentation, setups, and measurement standards. In Europe in particular, in situ spectral measurements remain highly heterogeneous. The goal of EUROSPEC Cost Action ES0930 was to promote the development of common measuring protocols and new instruments towards establishing best practices and standardization of these measurements. In this review we describe the background and main tradeoffs of in situ spectral measurements, review the main results of EUROSPEC Cost Action, and discuss the future challenges and opportunities of in situ spectral measurements for improved estimation of local and global estimates of GPP over terrestrial ecosystems.Peer reviewe

Sun-Induced Chlorophyll Fluorescence I: Instrumental Considerations for Proximal Spectroradiometers

Growing interest in the proximal sensing of sun‐induced chlorophyll fluorescence (SIF) has been boosted by space-based retrievals and up-coming missions such as the FLuorescence EXplorer (FLEX). The European COST Action ES1309 “Innovative optical tools for proximal sensing of ecophysiological processes” (OPTIMISE, ES1309; https://optimise.dcs.aber.ac.uk/) has produced three manuscripts addressing the main current challenges in this field. This article provides a framework to model the impact of different instrument noise and bias on the retrieval of SIF; and to assess uncertainty requirements for the calibration and characterization of state-of-the-art SIF-oriented spectroradiometers. We developed a sensor simulator capable of reproducing biases and noises usually found in field spectroradiometers. First the sensor simulator was calibrated and characterized using synthetic datasets of known uncertainties defined from laboratory measurements and literature. Secondly, we used the sensor simulator and the characterized sensor models to simulate the acquisition of atmospheric and vegetation radiances from a synthetic dataset. Each of the sensor models predicted biases with propagated uncertainties that modified the simulated measurements as a function of different factors. Finally, the impact of each sensor model on SIF retrieval was analyzed. Results show that SIF retrieval can be significantly affected in situations where reflectance factors are barely modified. SIF errors were found to correlate with drivers of instrumental-induced biases which are as also drivers of plant physiology. This jeopardizes not only the retrieval of SIF, but also the understanding of its relationship with vegetation function, the study of diel and seasonal cycles and the validation of remote sensing SIF products. Further work is needed to determine the optimal requirements in terms of sensor design, characterization and signal correction for SIF retrieval by proximal sensing. In addition, evaluation/validation methods to characterize and correct instrumental responses should be developed and used to test sensors performance in operational conditions

Ground-Based Optical Measurements at European Flux Sites: A Review of Methods, Instruments and Current Controversies

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

Sun-induced chlorophyll fluorescence I:Instrumental considerations for proximal spectroradiometers

Growing interest in the proximal sensing of sun-induced chlorophyll fluorescence (SIF) has been boosted by space-based retrievals and up-coming missions such as the FLuorescence EXplorer (FLEX). The European COST Action ES1309 “Innovative optical tools for proximal sensing of ecophysiological processes„ (OPTIMISE, ES1309; https://optimise.dcs.aber.ac.uk/) has produced three manuscripts addressing the main current challenges in this field. This article provides a framework to model the impact of different instrument noise and bias on the retrieval of SIF; and to assess uncertainty requirements for the calibration and characterization of state-of-the-art SIF-oriented spectroradiometers. We developed a sensor simulator capable of reproducing biases and noises usually found in field spectroradiometers. First the sensor simulator was calibrated and characterized using synthetic datasets of known uncertainties defined from laboratory measurements and literature. Secondly, we used the sensor simulator and the characterized sensor models to simulate the acquisition of atmospheric and vegetation radiances from a synthetic dataset. Each of the sensor models predicted biases with propagated uncertainties that modified the simulated measurements as a function of different factors. Finally, the impact of each sensor model on SIF retrieval was analyzed. Results show that SIF retrieval can be significantly affected in situations where reflectance factors are barely modified. SIF errors were found to correlate with drivers of instrumental-induced biases which are as also drivers of plant physiology. This jeopardizes not only the retrieval of SIF, but also the understanding of its relationship with vegetation function, the study of diel and seasonal cycles and the validation of remote sensing SIF products. Further work is needed to determine the optimal requirements in terms of sensor design, characterization and signal correction for SIF retrieval by proximal sensing. In addition, evaluation/validation methods to characterize and correct instrumental responses should be developed and used to test sensors performance in operational conditions

Hyperspectral remote sensing of a submerged macrophyte.

This study used to Spectron Industries SE-590 portable spectroradiometer to investigate a common Midwestern wetland species, Ceratophllum. Primary research objectives were: determine the effect of Ceratophllum on the composite spectral signal upwelling from a column of water, determine the death constraint for remote identification of Ceratophllum, and ascertain the presence of Ceratophllum in chlorophyll-laden water. Characteristic absorption features at 443 nm and 670 nm decreased with increasing depth and also as the algal chlorophyll concentrations increased. A wavelength shift in the NIR, associated with increasing depth was found to exist for water columns relatively free of algal chlorophyll as well as those containing denser concentrations of algal chlorophyll. The depth constraint was not determined and requires further study

Predicting evapotranspiration from sparse and dense vegetation communities in a semiarid environment using Ndvi from satellite and ground measurements

One of the most critical issues associated with using satellite data-based products to study and estimate surface energy fluxes and other ecosystem processes, has been the lack of frequent acquisition at a spatial scale equivalent to or finer than the footprint of field measurements. In this study, we incorporated continuous field measurements based on using Normalized difference vegetation index (NDVI) time series analysis of individual shrub species and transect measurements within 625 m2 size plots equivalent to the Landsat-5 Thematic Mapper spatial resolution. The NDVI system was a dual channel SKR-1800 radiometer that simultaneously measured incident solar radiation and upward reflectance in two broadband red and near-infrared channels comparable to Landsat-5 TM band 3 and band 4, respectively. The two study sites identified as Spring Valley 1 site (SV1) and Snake Valley 1 site (SNK1) were chosen for having different species composition, soil texture and percent canopy cover; NDVI time-series of greasewood (Sarcobatus vermiculatus) from the SV1 site allowed for clear distinction between the main phenological stages of the entire growing season during the period from January to November, 2007. Comparison of greasewood NDVI values between the two sites revealed a significant temporal difference associated with early canopy development and early dry down of greasewood at the SNK1 site. NDVI time series values were also significantly different between sagebrush (Artemisia tridentata ) and rabbitbrush (Chrysothamnus viscidiflorus) at SV1 as well as between the two bare soil types at the two sites, indicating the ability of the ground-based NDVI to distinguish between different plant species as well as between different desert soils based on their moisture level and color. The difference in phenological characteristics of greasewood between the two sites and between sagebrush, rabbitbrush and greasewood within the same site were not captured by the spatially integrated Landsat NDVI acquired during repeated overpasses. Greasewood NDVI from the SNK1 site produced significant correlations with many of the measured plant parameters, most closely with chlorophyll index (r = 0.97), leaf area index (r = 0.98) and leaf xylem water potential (r = 0.93). Whereas greasewood NDVI from the SV1 site produced lower correlations ( r = 0.89, r = 0.73), or non significant correlations (r = 0.32) with the same parameters, respectively. Total percent cover was estimated at 17.5% for SV1 and at 63% for SNK1; Transect measurements provided detailed information with regard to the spectral properties of shrub species and soil types, differentiating the two sites, which was not possible to discern with the spatial resolution of Landsat. Correlation between transect NDVI data and Landsat NDVI produced an r of 0.79. While correlation between transect NDVI data and ground-based NDVI sensors produced an r of 0.73. The linear regression equation between daily ET measured by the eddy covariance method and Landsat NDVI yielded a strong relationship (r = 0.88) for data combined across the experimental period (May to September) and across the two sites. The ET prediction equation was improved (r2 = 0.86) by introducing net solar radiation (Rn) which was the meteorological variable that had the highest prediction of ET (r2 = 0.82). A high correlation was found between weighted ground-based sensor NDVI estimates and Landsat derived NDVI at the pixel scale (r = 0.97) for the two study sites combined over time. While results from this study in scaling ground-based NDVI measurements and estimating ET were very promising, further verification and improvement is needed to determine the performance level of this approach over larger heterogeneous areas and over extended time periods

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