Today, virtually everything, from natural phenomena to complex artificial and physical systems, can be measured and the resulting information collected, stored and analyzed in order to gain new... Show moreToday, virtually everything, from natural phenomena to complex artificial and physical systems, can be measured and the resulting information collected, stored and analyzed in order to gain new insight. This thesis shows how complex systems often exhibit diverse behavior at different temporal scales, and that data mining methods should be able to cope with the multiple resolutions (scales) at the same time in order to fully understand the data at hand and extract useful information from it. Under these assumptions, we introduce novel data mining and visualization methods for large time series data collected from complex physical systems. In particular, we focus on three fundamental problems: the detection of multi-scale patterns, the recognition of recurrent events, and the interactive visualization of massive time series data. We evaluate our methods on a real-world scenario provided by InfraWatch, a Structural Health Monitoring project centered around the management and analysis of data collected by a large sensor network deployed on a Dutch highway bridge. The application of our methods resulted in the identification of the relevant scales of analysis in the InfraWatch data (and other datasets), the detection of the different recurring motifs and the visualization of terabytes of time series data interactively. Show less
Land use change results from the interaction between the human and the natural system and therefore various scientific disciplines have developed paradigms and methods to study land use change.... Show moreLand use change results from the interaction between the human and the natural system and therefore various scientific disciplines have developed paradigms and methods to study land use change. However, these disciplinary approaches can only cover part of the complex system of land use change. The objective of this dissertation is to develop interdisciplinary methodologies to identify and integrate factors that are important in the land use system to describe and model the land use system in a comprehensive manner. The methodological challenges that are addressed in this study include bridging differences in spatial and temporal scales and organisational levels, identification of appropriate units of analysis, combining different disciplinary paradigms and developing new paradigms that unify the disciplines in one concept. The development of these methods is illustrated with a case study in a municipality in the Philippines, where in the past century large land use changes have taken place through commercial logging and expansion of agriculture. To make projections of future land use in the area models were constructed for the case study. In this dissertation it is the combination of approaches that have led to a greater understanding of the land use in the study area. Especially moving between empirical, inductive methods and theoretical, deductive methods has proven to be a useful approach to stimulate theory building. Show less
