Terrestrial ecosystems are essential to human well-being, but their future remains highly uncertain, as evidenced by the huge disparities in model projections of the land carbon sink. The existence of these disparities despite the recent explosion of novel data streams, including the TRY plant traits database, the Landsat archive, and global eddy covariance tower networks, suggests that these data streams are not being utilized to their full potential by the terrestrial ecosystem modeling community. Therefore, the overarching objective of my dissertation is to identify how these various data streams can be used to improve the precision of model predictions by constraining model parameters. In chapter 1, I use a hierarchical multivariate meta-analysis of the TRY database to assess the dependence of trait correlations on ecological scale and evaluate the utility of these correlations for constraining ecosystem model parameters. I find that global trait correlations are generally consistent within plant functional types, and leveraging the multivariate trait space is an effective way to constrain trait estimates for data-limited traits and plant functional types. My next two chapters assess the ability to measure traits using remote sensing by exploring the links between leaf traits and reflectance spectra. In chapter 2, I introduce a method for estimating traits from spectra via radiative transfer model inversion. I then use this approach to show that although the precise location, width, and quantity of spectral bands significantly affects trait retrieval accuracy, a wide range of sensor configurations are capable of providing trait information. In chapter 3, I apply this approach to a large database of leaf spectra to show that traits vary as much within as across species, and much more across species within a functional type than across functional types. Finally, in chapter 4, I synthesize the findings of the previous chapters to calibrate a vegetation model's representation of canopy radiative transfer against observed remotely-sensed surface reflectance. Although the calibration successfully constrained canopy structural parameters, I identify issues with model representations of wood and soil reflectance that inhibit its ability to accurately reproduce remote sensing observations.

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The Center for Disease Control and Prevention (CDC) released heat illness data which highlighted that ~29 heat stress hospitalizations and ~3 heat-related deaths occurred every day during the summer months within the US from years 2000 to 2014. Heatstroke- the most severe form of heat illness which oftentimes lead to death- has been cited to be entirely preventable if a timely intervention is introduced. This dissertation uses microwave radiometric thermometry to perform wireless non-invasive internal body temperature monitoring which can enable intervention methods that help to prevent deaths associated with heat-illness. Overall, this dissertation develops a comprehensive closed-form analytical radiometric model and validates the effectiveness of the comprehensive model through a controlled life-like human body temperature sensing experiment. Wireless sub-skin temperature data is predicted from a human tissue mimicking phantom testbed to within 1%. A generic isolated radiometer system equation is derived for all possible calibration source combinations. The generic isolated radiometer system equation predicts comparable results to that of an ideal simulation. While improved isolation decreases measurement uncertainty, it does not improve the accuracy of estimated noise temperatures using a perfectly-isolated radiometer system equation assumption. A highly reproducible tissue-mimicking biological phantom (bio-phantom) recipe (comprised of urethane, graphite powder, and a solvent) was developed to accurately emulate the electrical properties of actual dry human skin versus frequency up to 18 GHz. The developed solid state skin phantom begins in pourable liquid form and then cures at room temperature into a dry solid state mold. An in-plane electromagnetic bandgap structure was developed and integrated within an on-body inward facing spiral antenna design. The inclusion of the in-plane electromagnetic bandgap structure demonstrated a +2.64dB gain improvement in the antenna broadside and -8dB in the rear gain while in-contact with the body as compared to the conventional spiral antenna. Likewise, the measured main beam efficiency is improved from 54.43% for the conventional antenna to 86.36% for the EBG antenna. Two techniques based on signal-flow graph theory were derived to explain both the non-coherent steady-state radiative transfer and the coherent radiative transfer within multi-layered dielectric media with non-uniform temperatures and any number of stratified layers. Both models allow for the accurate characterization and sensing of the thermal emissions originating from subsurface tissue layers.

Plusieurs méthodes existent pour évaluer de manière opérationnelle l'éclairement solaire au sol à partir d'images acquises par satellite. Durant sa thèse soutenue en 2009 à MINES ParisTech, Oumbe a conçu une nouvelle méthode, Heliosat-4, faisant appel à des modèles numériques du transfert radiatif et à des approximations d'exécution rapide. La présente thèse vise à consolider ces résultats et à effectuer la validation complète de la méthode Heliosat-4. Elle s'inscrit dans une collaboration scientifique internationale dans les projets européens MACC (Monitoring Atmosphere Composition and Climate) et MACC-II.Oumbe a proposé une approximation de l'équation de transfert radiatif s'écrivant alors comme un produit de l'éclairement par ciel clair par un terme d'extinction dû aux nuages. Nous avons établi que les erreurs liées à cette approximation sont très faibles dans les conditions usuelles et qu'elle peut donc être utilisée dans Heliosat-4, ce qui en facilitera l'implémentation informatique ainsi que son fonctionnement opérationnelle.La méthode Heliosat-4 est donc ainsi composé de deux modèles composés d'abaques : McClear pour l'éclairement par ciel clair et McCloud pour l'extinction cet éclairement due aux nuages. A l'aide de mesures in-situ d'éclairements direct et diffus de référence, nous avons analysé finement les performances de Heliosat-4 selon différentes conditions. La qualité de la première version pré-opérationnelle de Heliosat-4 est jugée satisfaisante car elle permet des estimations d'éclairement global avec une précision de l'ordre de celles des méthodes existantes mais des estimations des composantes directe et diffuse sensiblement de meilleure qualité. / Several methods have been developed to assess operationally the surface solar irradiance from satellite images. During his PhD thesis presented in 2009 at MINES ParisTech, Oumbe has designed a new method using numerical radiative transfer model and fast approximations. The present PhD thesis aimed at consolidating these results and validating Heliosat-4. This work is the international scientific collaboration framework of the European-funded projects MACC (Monitoring Atmosphere Composition and Climate) and MACC-II.As a foundation of Heliosat-4, Oumbe has proposed an approximation of the radiative transfer equation by a product of clear-sky irradiance and a term describing the cloud extinction. We have established that estimation errors due to this approximation are very small in usual conditions and that this approximation may be adopted. It allows a convenient modular development of Heliosat-4 and eases its future operational use.The Heliosat-4 method is then composed of two abacus-based models: McClear for the irradiance under clear-sky and McCloud for the irradiance extinction due to clouds. With in-situ reference measurements of direct and diffuse irradiance, we have carried out deep performance analysis of Heliosat-4, under different conditions. The quality of this first preoperational version of Heliosat-4 is judged satisfactory as it enables estimations of global irradiance with the same level of quality of other existing methods in literature but also estimations of direct and diffuse irradiances with a noticeable better quality.

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Urbanisierungsprozesse beeinflussen die Funktionen natürlicher Ökosysteme signifikant. Bereitgestellte ökosystemare Leistungen unterliegen Veränderungen, die direkt die Lebensbedingungen des Menschen beeinflussen. Funktionale Freiflächen mit Baum- und Gehölzbeständen sind wichtige Bestandteile urbaner Ökosysteme und lindern lokal Einflüsse der Urbanisierung. Die Umweltbedingungen in der Stadt weichen von den natürlichen ab und mindern die Funktionsfähigkeit der Bäume. Gegenüber etablierten, terrestrischen Untersuchungen des Baumzustands ermöglicht die Fernerkundung räumlich und zeitlich flexible Vitalitätscharakterisierungen. In dieser Dissertation wird ein fernerkundlicher Ansatz zur Baumzustandserhebung erarbeitet. Bei Nutzung hyperspektraler Bilddaten werden biophysikalische und strukturelle Baumparameter mit dem quantitativen Ansatz der Strahlungstransfermodellierung (RTM) abgeleitet. Schwerpunkt dieser Arbeit war die Adaption der RTM auf einzelne Bäume. Hierzu wurden drei Anpassungen vorgenommen: die Korrektur höhenbedingter Bildpunktversätze, die Selektion von Bildelementen und die Nutzung eines geometrisch-optischen Modells, um Einflüsse der Kronentopographie zu korrigieren. Eine Validierung der Modelle und abgeleiteter Parameter basierte auf umfangreichen Geländeerhebungen. Beispielhaft wurde die weißblühende Rosskastanie, eine Hauptbaumart Berlins, untersucht. Ein Modelltest zeigte die Eignung der modifizierten RTM, die optischen Eigenschaften von Kastanien zu modellieren. Mit einer Sensitivitätsanalyse wurde der Einfluss spezifischer Baumeigenschaften auf die Modellergebnisse quantifiziert, was die Optimierung des Verfahrens ermöglichte. Durch Invertierung der Modelle konnten die vitalitätsrelevanten Parameter Chlorophyll- und Wassergehalt realistisch abgeleitet und in ein Baumkataster eingebunden werden. Damit leistet diese Dissertation einen Beitrag, das thematische Spektrum verfügbarer Biogeodaten zur Untersuchung stadtökologische Prozesse zu erweitern. / Urbanisation affects natural ecosystems functions significantly. This leads to changes in ecosystem services which are directly linked to human living conditions. Functional open spaces, especially when covered with wood and trees, are a major component of urban ecosystems and lessen the impact of urbanisation. Environmental conditions of urban areas are fare away from non urban, natural ones. The functionality of trees decreases as a consequence of these unfavourable conditions. In comparison to terrestrial surveys, remote sensing enables spatially and temporally flexible descriptions of tree vitality. In the present work a remote sensing based approach to investigate conditions of urban trees was developed. Radiative transfer models (RTM) were used to derive biophysical and structural parameters from hyperspectral data. In order to adapt the modelling approach to single trees three modifications were made: a) the correction of pixel shifts due to the height of trees and non-nadir view angles of the sensor; b) the selection of spectrally pure pixels; c) the correction of albedo effects induced by crown geometry. A detailed validation of the models and the estimated parameters is performed based on data of an extensive ground survey. Being one of Berlin’s main tree species, the horse chestnut (lat. Aesculus hippocastanum) was exemplary investigated. An Evaluation of the modified RTM showed that they are able to model the optical properties of chestnut canopies. A sensitivity analysis was performed to quantify the impact of tree specific effects on the results of the modelling approach. The findings allowed an optimization of the method. Vitality parameters such as chlorophyll and water content could be realistically estimated by model inversion. Results were finally linked to an existing cadastral system. Results from this work help widen the thematic spectrum of environmental biogeodata applications and investigating multiple processes of urban ecology.