Crustal Deformation on the Northeastern Margin of the Tibetan Plateau from Continuous GPS Observations

We installed 10 continuous Global Positioning System (GPS) stations on the northeast margin of the Tibetan Plateau at the end of 2012, in order to qualitatively investigate strain accumulation across the Liupanshan Fault (LPSF). We integrated our newly built stations with 48 other existing GPS stations to provide new insights into three-dimensional tectonic deformation. We employed white plus flicker noise model as a statistical model to obtain realistic velocities and corresponding uncertainties in the ITRF2014 and Ordos-fixed reference frame. The total velocity decrease from northwest to southeast in the Longxi Block (LXB) was 5.3 mm/yr within the range of 200 km west of the LPSF on the horizontal component. The first-order characteristic of the vertical crustal deformation was uplift for the northeastern margin of the Tibetan Plateau. The uplift rates in the LXB and the Ordos Block (ORB) were 1.0 and 2.0 mm/yr, respectively. We adopted an improved spherical wavelet algorithm to invert for multiscale strain rates and rotation rates. Multiscale strain rates showed a complex crustal deformation pattern. A significant clockwise rotation of about 30 nradians/yr (10−9 radians/year) was identified around the Dingxi. Localized strain accumulation was determined around the intersectional region between the Haiyuan Fault (HYF) and the LPSF. The deformation pattern across the LFPS was similar to that of the Longmengshan Fault (LMSF) before the 2008 Wenchuan MS 8.0 earthquake. Furthermore, according to the distributed second invariant of strain rates at different spatial scale, strain partitioning has already spatially localized along the Xiaokou–Liupanshan–Longxian–Baoji fault belt (XLLBF). The tectonic deformation and localized strain buildup together with seismicity imply a high probability for a potential earthquake in this zone

Portraying urban diversity patterns through exploratory data analysis

This thesis analyzes the complexity of the urban system, being described with multiple variables that represent the environmental, economic, and social characters of the city. The portrayal of the urban diversity and its relationship with a better response of the city to disturbances, hence to its sustainability, is the main motivation of the study. Certainly, this thesis aims to provide theoretical knowledge through the application of statistical and computational methodologies that are developed progressively in its chapters. Beginning with the introduction, which draws the city as an abstract urban system and reviews the concepts and measures of diversity within the theoretical frameworks of sustainability, urban ecology, and complex systems theory. Afterward, the city of Barcelona is introduced as the case study: it is constituted by a set of districts and represented by an information system that contains temporal measurements of multiple environmental, economic, and social variables. A first approach to the sustainability of the city is made with the entropy of information as a measure of the urban system's diversity. But the fundamental contribution of the thesis focuses on the application of loratory Multivariate Analysis (EMA) to the urban system: Principal Component Analysis (PCA), Multiple Factorial Analysis (MFA), and Hierarchical Cluster Analysis (HCA). From this EMA approach, diversity is analyzed by identifying the similarity -or dissimilarity- between the different parts that make up the urban system. Some other techniques based on computer science and physics are proposed to evaluate the temporal transformation of the urban system, understood as a three-dimensional data cloud that gradually deforms. Differentiated characters and distinctive functions of districts are identifiable in the EMA application to the case study. Moreover, the temporal dependency of the dataset reveals information about the district's differentiation or homogenization trends. Finally, the conclusions of the most relevant results are presented and some future lines of research are proposed.Esta tesis analiza la complejidad del sistema urbano, descrito con múltiples variables que representan las características ambientales, económicas y sociales de la ciudad. La motivación fundamental para emprender este estudio consiste en describir la diversidad de la ciudad y su relación con una mejor respuesta a perturbaciones y amenazas, y por lo tanto, a su sostenibilidad. La tesis plantea aportar conocimiento teórico mediante la aplicación de metodologías estadísticas y computacionales que se desarrollan progresivamente en sus capítulos. En la introducción se presenta la abstracción de la ciudad como un sistema urbano, y se hace una revisión de los conceptos y medidas de la diversidad dentro de los marcos teóricos de la sostenibilidad, la ecología urbana y la teoría de los sistemas complejos. Posteriormente, se introduce el sistema urbano de la ciudad de Barcelona, constituido por un conjunto de distritos y representado mediante un sistema de información que contiene mediciones temporales de múltiples variables ambientales, económicas y sociales. Se hace una primera aproximación a la sostenibilidad de la ciudad empleando la entropía de la información como medida de diversidad del sistema urbano. Pero el aporte fundamental de la tesis se centra en la aplicación del Análisis Exploratorio Multivariante (EMA) en el sistema urbano: Análisis de Componentes principales (PCA), Análisis Factorial Múltiple (MFA) y Análisis de Agrupamiento Jerárquico (HCA). Desde dicho enfoque se analiza la diversidad identificando la similaridad -o disimilaridad- entre las distintas partes que componen el sistema urbano. Se plantean también algunas de las técnicas de las ciencias de la computación y la física para evaluar la transformación temporal del sistema urbano, entendido como una nube de datos tridimensionales que se deforma gradualmente. En el análisis del estudio de caso se identifican características diferenciadas y funciones distintivas de los distritos. Además, la dependencia temporal del conjunto de datos revela información sobre las tendencias de diferenciación u homogeneización de los distritos. Finalmente, se exponen las conclusiones de los resultados más relevantes y se enuncian algunas líneas futuras de investigaciónesPostprint (published version