Um dos tópicos mais importantes na análise de demanda por transportes é a relação entre as necessidades individuais de realização de atividades geograficamente distribuídas, a estrutura urbana, as características individuais e domiciliares, o sistema de transporte e as diferenças no comportamento relacionado a viagens. Isto motivou o desenvolvimento desta pesquisa, que tem como objetivo principal analisar o comportamento individual subjacente ao encadeamento de viagens sob a perspectiva de três grupos de variáveis: (1) participação em atividades; (2) características socioeconômicas; e (3) uso do solo. Há dois objetivos secundários, fundamentais para se atingir a finalidade do trabalho: (a) propor um conjunto de variáveis de uso do solo; e (b) testar a significância do grupo de variáveis ora proposto. Este trabalho baseou-se nos dados da pesquisa origem-destino de 1997 da região metropolitana de São Paulo, sendo extraídas e analisadas seis amostras finais que foram caracterizadas por setor econômico (no caso de trabalhadores) e grau de instrução (no caso de estudantes). Com utilização conjunta de técnicas de análise multivariadas, confirmatórias e exploratórias, foi possível representar a variável dependente (Análise de Cluster), bem como encontrar relações entre variáveis envolvidas (Árvore de Decisão) e, finalmente, mensurar a significância estatística das variáveis independentes (Regressão Linear Múltipla). Através dos resultados obtidos, foi possível analisar a influência dos três grupos de variáveis na seqüência de viagens: (1) variáveis socioeconômicas (renda familiar, usa vale transporte, nº provável de carteiras de habilitação no domicílio, idade, nº de automóveis no domicílio) afetam principalmente a seqüência de modos de transporte utilizados durante as viagens; (2) participação em atividades (estuda, trabalha) interfere na seqüência de motivos de viagem; e, enfim, (3) variáveis de uso do solo (parcela acumulada de empregos ou escolas por faixas de distância a partir do centróide da zona de residência) influenciam a seqüência de destinos escolhidos. Espera-se que o presente trabalho constitua uma contribuição ao meio acadêmico, tanto em termos de representação da intensidade e distribuição geográfica das atividades no meio urbano (variáveis de uso do solo), quanto em relação à influência de tais variáveis nos deslocamentos dos indivíduos. / One of the most important topics in transportation demand is the relationship between individual needs to carry out geographically distributed activities, urban configuration, individual and household characteristics, transportation system and travel behavior. For that reason, the main aim of this work is to analyze the individual trip-chaining behavior in terms of three variables groups: (1) activity participation; (2) socioeconomic characteristics; and (3) land use. There are also two secondary objectives derived from the main objective: (a) to propose one set of land use variables; and (b) to verify the statistical significance of the created land use group variables. This work was based on the origin-destination survey carried out in the São Paulo metropolitan area in 1997, from which six final samples were extracted, analyzed and characterized by economic sector (for workers) and level of education (for students). Applying multivariate analysis techniques, confirmatory and exploratory, it was possible to represent the dependent variable (Cluster Analysis), as well as to find relationships between the concerned variables (Decision Tree) and, finally, to measure the statistical significance of the independent variables (Multiple Regression). From the results, it was possible to analyze the influence of the three variables groups on trip-chaining: (1) socioeconomic variables (household income, transit voucher use, probable number of driver licenses per household, age, car-ownership) affect the travel mode sequence used for the trips; (2) activity participation (study, work) has an effect on the trip purpose sequence; and (3) land use variables (accumulated proportion of jobs or schools by distance buffers starting from the residence zone centroid) influence the sequence of chosen destinations. It is expected that the present work could be a contribution to the scientific community for the representation of the activities level and their geographic distribution in the urban configuration (land use variables), and the influence of such variables on individuals displacements.

Obtaining an accurate estimate of a land-cover classifier's performance over a wide geographic area is a challenging problem due to the need to generate the ground truth that covers the entire area that may be thousands of square kilometers in size. The current best approach constructs a testing dataset by drawing samples randomly from the entire area --- with a human supplying the true label for each such sample --- with the hope that the selections thus made statistically capture all of the data diversity in the area. A major shortcoming of this approach is that it is difficult for a human to ensure that the information provided by the next data element chosen by the random sampler is non-redundant with respect to the data already collected. In order to reduce the annotation burden, it makes sense to remove any redundancies from the entire dataset before presenting its samples to a human for annotation. This dissertation presents a framework that uses a combination of clustering and compression to create a concise-set representation of the land-cover data for a large geographic area. Whereas clustering is achieved by applying Locality Sensitive Hashing (LSH) to the data elements, compression is achieved through choosing a single data element to represent a given cluster. This framework reduces the annotation burden on the human and makes it more likely that the human would persevere during the annotation stage. We validate our framework experimentally by comparing it with the traditional random sampling approach using WorldView2 satellite imagery.

Um dos tópicos mais importantes na análise de demanda por transportes é a relação entre as necessidades individuais de realização de atividades geograficamente distribuídas, a estrutura urbana, as características individuais e domiciliares, o sistema de transporte e as diferenças no comportamento relacionado a viagens. Isto motivou o desenvolvimento desta pesquisa, que tem como objetivo principal analisar o comportamento individual subjacente ao encadeamento de viagens sob a perspectiva de três grupos de variáveis: (1) participação em atividades; (2) características socioeconômicas; e (3) uso do solo. Há dois objetivos secundários, fundamentais para se atingir a finalidade do trabalho: (a) propor um conjunto de variáveis de uso do solo; e (b) testar a significância do grupo de variáveis ora proposto. Este trabalho baseou-se nos dados da pesquisa origem-destino de 1997 da região metropolitana de São Paulo, sendo extraídas e analisadas seis amostras finais que foram caracterizadas por setor econômico (no caso de trabalhadores) e grau de instrução (no caso de estudantes). Com utilização conjunta de técnicas de análise multivariadas, confirmatórias e exploratórias, foi possível representar a variável dependente (Análise de Cluster), bem como encontrar relações entre variáveis envolvidas (Árvore de Decisão) e, finalmente, mensurar a significância estatística das variáveis independentes (Regressão Linear Múltipla). Através dos resultados obtidos, foi possível analisar a influência dos três grupos de variáveis na seqüência de viagens: (1) variáveis socioeconômicas (renda familiar, usa vale transporte, nº provável de carteiras de habilitação no domicílio, idade, nº de automóveis no domicílio) afetam principalmente a seqüência de modos de transporte utilizados durante as viagens; (2) participação em atividades (estuda, trabalha) interfere na seqüência de motivos de viagem; e, enfim, (3) variáveis de uso do solo (parcela acumulada de empregos ou escolas por faixas de distância a partir do centróide da zona de residência) influenciam a seqüência de destinos escolhidos. Espera-se que o presente trabalho constitua uma contribuição ao meio acadêmico, tanto em termos de representação da intensidade e distribuição geográfica das atividades no meio urbano (variáveis de uso do solo), quanto em relação à influência de tais variáveis nos deslocamentos dos indivíduos. / One of the most important topics in transportation demand is the relationship between individual needs to carry out geographically distributed activities, urban configuration, individual and household characteristics, transportation system and travel behavior. For that reason, the main aim of this work is to analyze the individual trip-chaining behavior in terms of three variables groups: (1) activity participation; (2) socioeconomic characteristics; and (3) land use. There are also two secondary objectives derived from the main objective: (a) to propose one set of land use variables; and (b) to verify the statistical significance of the created land use group variables. This work was based on the origin-destination survey carried out in the São Paulo metropolitan area in 1997, from which six final samples were extracted, analyzed and characterized by economic sector (for workers) and level of education (for students). Applying multivariate analysis techniques, confirmatory and exploratory, it was possible to represent the dependent variable (Cluster Analysis), as well as to find relationships between the concerned variables (Decision Tree) and, finally, to measure the statistical significance of the independent variables (Multiple Regression). From the results, it was possible to analyze the influence of the three variables groups on trip-chaining: (1) socioeconomic variables (household income, transit voucher use, probable number of driver licenses per household, age, car-ownership) affect the travel mode sequence used for the trips; (2) activity participation (study, work) has an effect on the trip purpose sequence; and (3) land use variables (accumulated proportion of jobs or schools by distance buffers starting from the residence zone centroid) influence the sequence of chosen destinations. It is expected that the present work could be a contribution to the scientific community for the representation of the activities level and their geographic distribution in the urban configuration (land use variables), and the influence of such variables on individuals displacements.

El estudio de las anisotropías de la Radiación Cósmica del Fondo de Microondas es una de las piedras de toque de la Cosmología actual. Una fase importante de dicho estudio consiste en el análisis previo de los datos mediante técnicas deprocesado estadístico que permiten identificar, separar y estudiar de forma independiente las diferentes componentes físicas que contribuyen a la emisión del cielo. En esta Tesis se propone una nueva técnica de filtrado, los Filtros Adaptados a la Escala, que permite detectar la emisión de fuentes compactas(galaxias y cúmulos de galaxias) de forma robusta atendiendo alas particularidades de su estructura espacial a pequeña escala.Los Filtros Adaptados a la Escala se introducen de forma teórica y posteriormente son aplicados a simulaciones realistas que reproducen las condiciones de la futura misión de la AgenciaEspacial Europea "Planck", tanto en el régimen unidimensional como en imágenes bidimensionales en una o varias frecuencias (según se trate de detección de galaxias o de cúmulos de galaxias). Se concluye que los Filtros Adaptados a la Escalaconstituyen una herramienta potente y robusta para la detección de fuentes compactas en imágenes astronómicas. / The study of the anisotropies of the Cosmic Microwave Background (CMB) is one of the milestones of modern Cosmology. Before the analysis of the CMB itself, it is importantto apply statistical tools to the data in order to identify and separate the different physical components that contribute to the sky emission at microwave wavelengths. In this Thesis a newlinear filter is proposed, the so-called Scale Adaptive Filter (SAF), that takes into account the characteristic spatial signature of compact sources (namely galaxies and galaxy clusters) inorder to optimise the detection of such sources in CMB data.The SAF is firstly theoretically introduced and then it is applied to realistic simulated CMB data as they will be observed by the upcoming ESA's Planck Mission. The considered cases includeboth unidimensional and bidimensional data sets at one single frequency (for the case of the detection of radio and infrared galaxies) or considering several frequency channels (for thecase of the detection of galaxy clusters via the Sunyaev-Zel'dovich effect). The SAF is found to be a robust and powerful tool for the detection of compact sources in astronomical images.

<p dir="ltr">In the context of a Human-in-the-Loop (HITL) system, the accuracy of reachability analysis plays a significant role in ensuring the safety and reliability of HITL systems. In addition, one can avoid unnecessary conservativeness by explicitly considering human control behavior compared to those methods that rely on the system dynamics alone. One possible approach is to use a Gaussian Mixture Model (GMM) to encode human control behavior using the Expectation-Maximization (EM) algorithm. However, relatively few works consider the admissible control input ranges due to physical limitations when modeling human control behavior. This could make the following reachability analysis overestimate the system's capability, thereby affecting the performance of the HITL system. To address this issue, this work presents a constrained stochastic reachability analysis algorithm that can explicitly account for the admissible control input ranges. By confining the ellipsoidal confidence region of each Gaussian component using Sequential Quadratic Programming (SQP), we probabilistically constrain the GMM as well as the corresponding stochastic reachable sets. A comprehensive mathematical analysis of how the constrained GMM can affect the stochastic reachable sets is provided in this work. Finally, the proposed stochastic reachability analysis algorithm is validated via an illustrative numerical example.</p>

Theories of how galaxies form and evolve depend greatly on constraints provided by observations. However, when those observations come from different datasets, systematic offsets may occur. This causes difficulties measuring variations in parameters between filters. In this thesis I present the variation in total luminosity density with wavelength in the nearby Universe (z<0.1), produced from a consistent reanalysis of NIR and optical observations, taken from the MGC, UKIDSS and SDSS surveys. I derive luminosity distributions, best-fitting Schechter function parameterisations and total luminosity densities in ugrizYJHK, and compare the variation in luminosity density with cosmic star formation history (CSFH) and initial mass function (IMF) models. I examine the r band luminosity distribution produced using different aperture definitions, the joint luminosity- surface brightness (bivariate brightness) distribution in ugrizYJHK, comparing them to previously derived distributions, and how the total luminosity density varies with wavelength when surface brightness incompleteness is accounted for. I find the following results. (1) The total luminosity density calculated using a non-Sersic (e.g. Kron or Petrosian) aperture is underestimated by at least 15%, (2) Changing the detection threshold has a minor effect on the best-fitting Schecter parameters, but the choice of Kron or Petrosian apertures causes an offset between datasets, regardless of the filter used to define the source list, (3) The decision to use circular or elliptical apertures causes an offset in M* of 0.20 mag, and best-fitting Schechter parameters from total magnitude photometric systems have a flatter faint-end slope than Kron or Petrosian photometry, (4) There is no surface brightness distribution evolution with luminosity for luminous galaxies, but at fainter magnitudes the distribution broadens and the peak surface brightness dims. A Choloniewski function that is modified to account for this surface brightness evolution fits the bivariate-brightness distribution better than an unmodified Choloniewski function, (5) The energy density per unit interval, vf(v) derived using MGC and GAMA samples agrees within 90% confidence intervals, but does not agree with predictions using standard CSFH and IMF models. Possible improvements to the data and alterations to the theory are suggested.

Indiana University-Purdue University Indianapolis (IUPUI) / Understanding the mechanical properties of peripheral nerves is essential for chronically implanted device design. The work in this thesis aimed to understand the relationship between local deformation responses to global strain changes in peripheral nerves. A custom-built mechanical testing rig and sample holder enabled an improved cyclical uniaxial tensile testing environment on rabbit sciatic nerves (N=5). A speckle was placed on the surface of the nerve and recorded with a microscope camera to track local deformations. The development of a semi-automated digital image processing algorithm systematically measured local speckle dimension and nerve diameter changes. Combined with the measured force response, local and global strain values constructed a stress-strain relationship and corresponding elastic modulus. Preliminary exploration of models such as Fung and 2-Term Mooney-Rivlin confirmed the hyperelastic nature of the nerve. The results of strain analysis show that, on average, local strain levels were approximately five times smaller than globally measured strains; however, the relationship was dependent on global strain magnitude. Elastic modulus values corresponding to ~9% global strains were 2.070 ± 1.020 MPa globally and 10.15 ± 4 MPa locally. Elastic modulus values corresponding to ~6% global strains were 0.173 ± 0.091 MPa globally and 1.030 ± 0.532 MPa locally.

<div>In this thesis, we explore different methods to enhance the safety and robustness for autonomous systems. We achieve this goal using concepts and tools from reachability analysis and control barrier functions. We first take on a multi-player reach-avoid game that involves two teams of players with competing objectives, namely the attackers and the defenders. We analyze the problem and solve the game from the attackers' perspectives via a moving horizon approach. The resulting solution provides a safety guarantee that allows attackers to reach their goals while avoiding all defenders. </div><div><br></div><div>Next, we approach the problem of target re-association after long-term occlusion using concepts from reachability as well as Bayesian inference. Here, we set out to find the probability identity matrix that associates the identities of targets before and after an occlusion. The solution of this problem can be used in conjunction with existing state-of-the-art trackers to enhance their robustness.</div><div><br></div><div>Finally, we turn our attention to a different method for providing safety guarantees, namely control barrier functions. Since the existence of a control barrier function implies the safety of a control system, we propose a framework to learn such function from a given user-specified safety requirement. The learned CBF can be applied on top of an existing nominal controller to provide safety guarantees for systems.</div>

Analyzing the structure of a dataset is a challenging problem in high-dimensions as the volume of the space increases at an exponential rate and typically, data becomes sparse in this high-dimensional space. This poses a significant challenge to machine learning methods which rely on exploiting structures underlying data to make meaningful inferences. This dissertation proposes the <i>n</i>-TARP method as a building block for high-dimensional data analysis, in both supervised and unsupervised scenarios.<div><br></div><div>The basic element, <i>n</i>-TARP, consists of a random projection framework to transform high-dimensional data to one-dimensional data in a manner that yields point separations in the projected space. The point separation can be tuned to reflect classes in supervised scenarios and clusters in unsupervised scenarios. The <i>n</i>-TARP method finds linear separations in high-dimensional data. This basic unit can be used repeatedly to find a variety of structures. It can be arranged in a hierarchical structure like a tree, which increases the model complexity, flexibility and discriminating power. Feature space extensions combined with <i>n</i>-TARP can also be used to investigate non-linear separations in high-dimensional data.<br></div><div><br></div><div>The application of <i>n</i>-TARP to both supervised and unsupervised problems is investigated in this dissertation. In the supervised scenario, a sequence of <i>n</i>-TARP based classifiers with increasing complexity is considered. The point separations are measured by classification metrics like accuracy, Gini impurity or entropy. The performance of these classifiers on image classification tasks is studied. This study provides an interesting insight into the working of classification methods. The sequence of <i>n</i>-TARP classifiers yields benchmark curves that put in context the accuracy and complexity of other classification methods for a given dataset. The benchmark curves are parameterized by classification error and computational cost to define a benchmarking plane. This framework splits this plane into regions of "positive-gain" and "negative-gain" which provide context for the performance and effectiveness of other classification methods. The asymptotes of benchmark curves are shown to be optimal (i.e. at Bayes Error) in some cases (Theorem 2.5.2).<br></div><div><br></div><div>In the unsupervised scenario, the <i>n</i>-TARP method highlights the existence of many different clustering structures in a dataset. However, not all structures present are statistically meaningful. This issue is amplified when the dataset is small, as random events may yield sample sets that exhibit separations that are not present in the distribution of the data. Thus, statistical validation is an important step in data analysis, especially in high-dimensions. However, in order to statistically validate results, often an exponentially increasing number of data samples are required as the dimensions increase. The proposed <i>n</i>-TARP method circumvents this challenge by evaluating statistical significance in the one-dimensional space of data projections. The <i>n</i>-TARP framework also results in several different statistically valid instances of point separation into clusters, as opposed to a unique "best" separation, which leads to a distribution of clusters induced by the random projection process.<br></div><div><br></div><div>The distributions of clusters resulting from <i>n</i>-TARP are studied. This dissertation focuses on small sample high-dimensional problems. A large number of distinct clusters are found, which are statistically validated. The distribution of clusters is studied as the dimensionality of the problem evolves through the extension of the feature space using monomial terms of increasing degree in the original features, which corresponds to investigating non-linear point separations in the projection space.<br></div><div><br></div><div>A statistical framework is introduced to detect patterns of dependence between the clusters formed with the features (predictors) and a chosen outcome (response) in the data that is not used by the clustering method. This framework is designed to detect the existence of a relationship between the predictors and response. This framework can also serve as an alternative cluster validation tool.<br></div><div><br></div><div>The concepts and methods developed in this dissertation are applied to a real world data analysis problem in Engineering Education. Specifically, engineering students' Habits of Mind are analyzed. The data at hand is qualitative, in the form of text, equations and figures. To use the <i>n</i>-TARP based analysis method, the source data must be transformed into quantitative data (vectors). This is done by modeling it as a random process based on the theoretical framework defined by a rubric. Since the number of students is small, this problem falls into the small sample high-dimensions scenario. The <i>n</i>-TARP clustering method is used to find groups within this data in a statistically valid manner. The resulting clusters are analyzed in the context of education to determine what is represented by the identified clusters. The dependence of student performance indicators like the course grade on the clusters formed with <i>n</i>-TARP are studied in the pattern dependence framework, and the observed effect is statistically validated. The data obtained suggests the presence of a large variety of different patterns of Habits of Mind among students, many of which are associated with significant grade differences. In particular, the course grade is found to be dependent on at least two Habits of Mind: "computation and estimation" and "values and attitudes."<br></div>

[ES] El objetivo 2 para el desarrollo sostenible de la ONU es hambre cero. Concretamente, se trata de poner fin al hambre, lograr la seguridad alimentaria (SA) y la mejora de la nutrición y promover la agricultura sostenible. Hay que destacar que la inseguridad alimentaria no es un problema exclusivo de países en desarrollo, sino que en los países llamados desarrollados parte de la población tiene problemas para garantizar una nutrición adecuada. Por otro lado, si bien hasta la fecha gran parte del debate sobre la SA se ha centrado en aspectos relacionados con la accesibilidad y la producción de alimentos, se observa una tendencia hacia un concepto más integral de la SA que abarca también los cambios ambientales globales. Por esta razón, investigadores, gobiernos y organismos internacionales están proponiendo medidas de diversa índole, enfocadas en garantizar la seguridad alimentaria y nutricional de la población, por un lado, y en contrarrestar los impactos negativos que las actividades de producción y consumo de alimentos tienen sobre el medio ambiente y el cambio climático. En este sentido, el registro de datos relacionados con variables económicas y medioambientales, junto al conocimiento de expertos en estas áreas y el uso de herramientas de estadística aplicada, han contribuido a que, a partir de evidencias objetivas, se formalicen de una forma estructurada y coherente las acciones que pueden modificar el comportamiento social y económico de todos los agentes involucrados. En este contexto, la teoría económica en general, y la teoría del consumidor en particular, a partir del registro y procesado detallado de información estadística relacionada, han hecho posible analizar algunos aspectos de las actitudes, comportamientos y preferencias del consumidor. Dichos aspectos pueden ser utilizados como señales de las posibles reacciones que los consumidores tendrían en su demanda por algunos alimentos ante cambios en variables de mercado que no puede controlar, como los precios, o ante acciones de política pública que también pueden modificar sus decisiones de consumo tales como la aplicación de impuestos y/o subsidios, los cuales finalmente afectarán sus metas alimentarias y nutricionales. Por otro lado, el análisis de ciclo de vida (ACV) ha adquirido una gran fortaleza en términos de evaluación medioambiental. En concreto, el ACV en su variante consecuencial (ACV-C) presenta interés para la valoración de las posibles consecuencias sobre el medioambiente ante cambios exógenos en variables económicas o de política medioambiental. En la literatura relacionada con ACV-C se utilizan las elasticidades para conocer la denominada relación de sustitución entre productos alternativos. En general, una elasticidad es una medida cuantitativa que relaciona el cambio porcentual en términos de cantidades para una variable en particular con el cambio porcentual que tenga cualquier otra variable. De esta manera se pueden modelar los cambios que se presentan a corto y largo plazo en los indicadores medioambientales como consecuencia de cambios en variables como los precios o la cantidad de insumos utilizados en la producción de un bien o servicio. Ante este escenario, el objetivo de esta tesis es proponer nuevas metodologías para evaluar la seguridad alimentaria (SA) y la sostenibilidad ambiental asociada al consumo de alimentos, con el fin de promover una seguridad alimentaria sostenible. Los casos de estudio desarrollados se centrarán en España y se utilizarán herramientas metodológicas que involucren la aplicación de la teoría del consumidor, la perspectiva de ciclo de vida y algunos métodos estadísticos. El alcance del objetivo planteado se ha logrado a partir de cuatro objetivos secundarios, y cada uno de ellos ha quedado reflejado en sendos capítulos de la tesis, de los cuales dos se han concentrado en analizar la seguridad alimentaria y los dos restantes en los aspectos medioambientales. / [CAT] El segon dels Objectius per al Desenvolupament Sostenible de la ONU és fam zero. Concretament, es tracta de posar fi a la fam, aconseguir la seguretat alimentària (SA) i millorar la nutrició i promoure la agricultura sostenible. Cal destacar que la inseguretat alimentària no és un problema exclusiu de països en desenvolupament, sinó que als països anomenats desenvolupats part de la població té problemes per a garantir una nutrició adient. Per altra banda, encara que gran part del debat al voltant de la SA s'ha centrat en aspectes relacionats amb l'accessibilitat i la producció d'aliments, s'observa una tendència cap a un concepte més integral de la SA que abasta també els canvis ambientals globals. Per aquesta raó, investigadors, governs i organismes internacionals estan proposant mesures de diversa índole, enfocades a garantir la seguretat alimentària i nutricional de la població, d'una banda, i a contrarestar els impactes negatius que les activitats de producció i consum d'aliments tenen sobre el medi ambient i el canvi climàtic. En aquest sentit, el registre de dades relacionades amb variables econòmiques i ambientals, conjuntament amb el coneiximent d'experts en aquestes àrees i l'ús d'eines d'estadística aplicada, han contribuït a que a partir de evidències objectives es formalitzen de forma estructurada i coherent les accions que poden modificar el comportament social i econòmic de tots els agents involucrats. En aquest context, la teoria econòmica en general, i la teoria del consumidor en particular, a partir del registre i processament detallat d'informació estadística relacionada, han fet possible analitzar alguns aspectes de les actituds, comportaments i preferències del consumidor. Aquests aspectes poden ser utilitzats com a senyals de les possibles reaccions que els consumidors tindrien en la seua demanda per alguns aliments davant canvis en variables de mercat que no pot controlar, com ara els preus, o davant accions de política pública que també poden modificar les seues decisions de consum, tals com l'aplicació d'impostos i/o subsidis, els quals finalment afectaran les seues metes alimentàries i nutricionals. D'altra banda, l'anàlisi de cicle de vida (ACV) ha adquirit una gran fortalesa per a la avaluació ambiental. En concret, l'ACV en la seua variant conseqüencial (ACV-C) presenta interès per a la valoració de les possibles conseqüències sobre el mediambient davant canvis exògens en variables econòmiques o de política medioambiental. En la literatura relacionada amb l'ACV-C s'utilitzen paràmetres econòmics como ara les elasticitats, per a conèixer la denominada relació de substitució entre productes alternatius. En general, una elasticitat es una mesura quantitativa que relaciona el canvi percentual en quant a quantitats d'una variable en particular amb el canvi percentual que té qualsevol altra variable. D'aquesta manera es poden modelar els canvis que es presenten a curt i llarg termini em els indicadors mediambientals a conseqüència de canvis en variables como ara els preus o la quantitat d'inputs utilitzats en la producció d'un bé o servei. Davant d'aquest escenari, l'objectiu d'aquesta tesi es proposar noves metodologies per a avaluar la seguretat alimentària (SA) i la sostenibilitat ambiental associada al consum d'aliments, amb la fi de promoure una seguretat alimentària sostenible. Els casos d'estudi desenvolupats se centraran en Espanya, i s'utilitzaran eines metodològiques que involucren l'aplicació de la teoria del consumidor, la perspectiva de cicle de vida i alguns mètodes estadístics. L'abast del objectiu plantejat s'ha aconseguit a partir de quatre objectius secundaris, i cadascun d'ells ha quedat reflectit en respectius capítols de la tesi, dels cuals dos s'han centrat en analitzar la seguretat alimentària, i els dos restants en els aspectes medioambientals. / [EN] The second of the UNO's Sustainable Development Goals is zero hunger. The aim is to end hunger, achieve food security (FS) and improved nutrition and promote sustainable agriculture. It must be highlighted that food insecurity is not a problem exclusively for developing countries, but in the so-called developed countries, part of the population has also problems to achieve adequate nutrition. On the other hand, although to date much of the debate on FS has focused on aspects related to accessibility and food production, there is a trend towards a more comprehensive concept of food security that also encompasses global environmental changes. Thus, researchers, governments, and international organizations as FAO are proposing various measures and focused on guaranteeing food and nutritional security of the population and, in addition, on counteracting the negative impacts that food production and consumption generate on the environment and climate change. Along these lines, the recording of economic and environmental data, together with experts' knowledge in these areas, and the use of applied statistics are fundamental so that, from objective evidence, actions to modify the economic and social behavior of the individuals involved be formulated in a structured and coherent way. In this context, the economic theory in general, and the consumer theory in particular, accompanied by detailed recording and processing of statistical information, have made possible to analyze many aspects related to the attitudes, behaviors, and preferences of consumers. These aspects may be used as signals of their possible consumers' demand reactions for some foods in the face of changes in market variables that they cannot control, such as food prices, or in the face of public policy actions that may also alter their decisions such as taxes and /or subsidies, which will ultimately affect your food and nutritional situation. On the other hand, Life Cycle Assessment (LCA) has gained great importance as to environmental assessment. Specifically, consequential LCA (C-LCA) arises as a tool to assess the potential consequences on the environment in view of exogenous changes in specific economic variables, or environmental policies. When reviewing the literature on C-LCA, elasticities are used to find out the so-called substitution ratio between alternative products. Generally, an elasticity is a quantitative measure that relates the percentage change of a specific variable with the percentage change of another variable. In this way, we can model short and long term changes of the environmental indicators as a consequence of changes of variables such as the price or the amount of inputs applied in the production of a good or service. Taking the foregoing, the objective of this dissertation is to propose new methodologies to evaluate Food Security (FS), and the environmental sustainability associated with food consumption, in order to promote a sustainable food security. The case studies developed will be focused on Spain, and methodological tools that involve the application of consumer theory, LCA, together with statistical methods will be used for this. The scope of the stated objective has been achieved from four secondary objectives, each of them reflected in respective chapters of this dissertation. Two of the chapters focus on analyzing food security, and the remaining two on environmental aspects. Initially, in the absence of FS measurement tools that allow the formulation of strategies in terms of regions or regional blocks, a new methodology for measuring food insecurity based on the dimensions of access and stability consumption is proposed and implemented in chapter 2. To this aim, the values of different price and income elasticities for nine animal sourced foods (ASF) are integrated by using quarterly data of for the period 2004-2015 in the 17 Spanish regions. The results / Forero Cantor, GA. (2020). Incorporación de consideraciones de estabilidad y sostenibilidad ambiental en la seguridad alimentaria. El caso de España [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/158733