(Cont.) Results indicate that the configuration of commuting spectrums mirror the changes in urban spatial structure in terms of job-housing proximity. In addition, the spatial variation, temporal change and regional differences in commuting can be significantly explained with job-housing proximity. Empirical results suggest that spatial decentralization pathways in Atlanta and Boston change the regional patterns of job-housing proximity, attracting people to commute longer distances. The relatively constrained spatial decentralization in Boston results in shorter commuting time and distance than in Atlanta. The empirical results point to a constrained and balanced vision of urban growth for achieving a commuting economy. Both urban growth management and transportation policies are needed to help achieve this vision.
Features modern research and methodology on the spread of infectious diseases and showcases a broad range of multi-disciplinary and state-of-the-art techniques on geo-simulation, geo-visualization, remote sensing, metapopulation modeling, cloud computing, and pattern analysis Given the ongoing risk of infectious diseases worldwide, it is crucial to develop appropriate analysis methods, models, and tools to assess and predict the spread of disease and evaluate the risk. Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases features mathematical and spatial modeling approaches that integrate applications from various fields such as geo-computation and simulation, spatial analytics, mathematics, statistics, epidemiology, and health policy. In addition, the book captures the latest advances in the use of geographic information system (GIS), global positioning system (GPS), and other location-based technologies in the spatial and temporal study of infectious diseases. Highlighting the current practices and methodology via various infectious disease studies, Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases features: Approaches to better use infectious disease data collected from various sources for analysis and modeling purposes Examples of disease spreading dynamics, including West Nile virus, bird flu, Lyme disease, pandemic influenza (H1N1), and schistosomiasis Modern techniques such as Smartphone use in spatio-temporal usage data, cloud computing-enabled cluster detection, and communicable disease geo-simulation based on human mobility An overview of different mathematical, statistical, spatial modeling, and geo-simulation techniques Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases is an excellent resource for researchers and scientists who use, manage, or analyze infectious disease data, need to learn various traditional and advanced analytical methods and modeling techniques, and become aware of different issues and challenges related to infectious disease modeling and simulation. The book is also a useful textbook and/or supplement for upper-undergraduate and graduate-level courses in bioinformatics, biostatistics, public health and policy, and epidemiology.
The study contributes in analytical description of spatial diffusion of fertility, in particular, influenced by labour movements of people between places of residence and work. It is assumed that the labour market has externality on the marriage market due to commuting, which, in turn, affects fertility. A model of spatial diffusion of fertility is based on assumption of global and local spillover effects. The global spillover effect, as shifts in fertility norms, is motivated by increasing variance of social interactions of an individual, when places of work and residence are different. One local spillover effect is in response to flows of earnings across space. Another mechanism is related to expected changes in probabilities to find a partner affected by differences in day and night population. The analytical model, in which the effects on fertility of the cited spillovers are decomposed, is constructed in the paper on the base of a model of the demand for children, spatial stock-flow model of a market, and a matching model with a sex imbalance or spatial mismatch as the probability of matching. Three sex imbalances, namely of night-, day-time population and an adjusted to sex imbalance of commuters to residents are empirically tested. Empirical evidence on municipal Swedish data for the period 1994–2008 does not provide any strong evidence of spatial diffusion of fertility. However, there are externalities of labour mobility on fertility due to changes of gender structure of population.
The recent availability of longitudinal data on individual trip making and activity behaviour has provided analysts with new insights into the structures and motives of daily life travel. Multi-week travel diary data-sets and GPS observations are exciting sources of information for the description and modelling of the variability of individual travel patterns. Through an analysis of these strong new data sets, this book questions what are the most suitable methodological tools to represent the structures of long-term travel behaviour. It also examines what the data tells us about the travellers' motives and looks at how planning should translate the findings into forecasting tools and transport strategies. In doing so, the multifaceted and ambiguous character of daily life travel is revealed, illustrating how, while sound routines in time and space seem to dominate daily life, individuals show a considerable amount of variability and flexibility in travel and activity behaviour.
This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16–18, 2016. Combining theoretical papers and applications by authors from around the globe, it summarises the latest research findings in the area of big spatial data and key problems related to its utilisation. Welcome to dawn of the big data era: though it’s in sight, it isn’t quite here yet. Big spatial data is characterised by three main features: volume beyond the limit of usual geo-processing, velocity higher than that available using conventional processes, and variety, combining more diverse geodata sources than usual. The popular term denotes a situation in which one or more of these key properties reaches a point at which traditional methods for geodata collection, storage, processing, control, analysis, modelling, validation and visualisation fail to provide effective solutions. >Entering the era of big spatial data calls for finding solutions that address all “small data” issues that soon create “big data” troubles. Resilience for big spatial data means solving the heterogeneity of spatial data sources (in topics, purpose, completeness, guarantee, licensing, coverage etc.), large volumes (from gigabytes to terabytes and more), undue complexity of geo-applications and systems (i.e. combination of standalone applications with web services, mobile platforms and sensor networks), neglected automation of geodata preparation (i.e. harmonisation, fusion), insufficient control of geodata collection and distribution processes (i.e. scarcity and poor quality of metadata and metadata systems), limited analytical tool capacity (i.e. domination of traditional causal-driven analysis), low visual system performance, inefficient knowledge-discovery techniques (for transformation of vast amounts of information into tiny and essential outputs) and much more. These trends are accelerating as sensors become more ubiquitous around the world.
The collection of chapters in Volume 43 Part B of Advances in Econometrics serves as a tribute to one of the most innovative, influential, and productive econometricians of his generation, Professor M. Hashem Pesaran.
According to UN estimates, approximately nearly half of the world's population now lives in cities and that figure is expected to rise to almost 70% by 2050. Cities now account for around 70% of worldwide greenhouse gas emissions, and this percentage is predicted to rise in the near future as a result of projected increases in global urbanization patterns. It is widely acknowledged that irrational urban planning and design can increase emissions while also exacerbating threats and risks, resulting in a slew of environmental issues such as urban heat islands, air pollution, flooding, amongst other issues, as well as environmental, social, and economic losses. Therefore, these concerns must be addressed promptly in order to cope up with these rising difficulties and make urban environments safer for residents. With the advancement of remote sensing technology and the use of current remote observation systems, urban data science, remote sensing, and artificial intelligence (AI), modeling and quantifying emergent difficulties in urban regions and urban systems have become easy. They aid in the quantitative analysis of urban shape, functions, and human behavior in cities. Harvesting data, developing models, and suggesting new methodologies will be aided by combining urban ecology with new breakthroughs in data science. This book is of great value to a diverse group of academicians, scientists, students, environmentalists, meteorologists, urban planners, remote sensing and GIS experts with a common interest in geospatial sciences within the earth environmental sciences, as well as human and social sciences.
This book focuses on the creation of space as an activity. The argument draws not only on aspects of movement in time, but also on a cultural and specifically social context influencing the creation of the spatial habitus. The book reconsiders existing theories of time and space in the field of urban planning and develops an updated account of spatial activity, experience and space-making. Recent developments in spatial practice, specifically related to new technologies, make this an important and timely task. Integrating spatial-temporal dynamics into the way we think about cities aids the implementation of sustainable forms of urban planning. The study is composed of two different case studies. One case is based on fieldwork tracking individual movement using GPS, the other case utilises data mined from Twitter. One of the key elements in the conclusion to this book is the definition of temporality as a status rather than a transition. It is argued that through repetitive practices as habitus, time has presence and agency in our everyday lives. This book is based on the work undertaken for a PhD at the Centre for Advanced Spatial Analysis and was and accepted as thesis by University College London in 2013.
An exploration of the ways that everyday life in the city is defined by commuting. We spend much of our lives in transit to and from work. Although we might dismiss our daily commute as a wearying slog, we rarely stop to think about the significance of these daily journeys. In Transit Life, David Bissell explores how everyday life in cities is increasingly defined by commuting. Examining the overlooked events and encounters of the commute, Bissell shows that the material experiences of our daily journeys are transforming life in our cities. The commute is a time where some of the most pressing tensions of contemporary life play out, striking at the heart of such issues as our work-life balance; our relationships with others; our sense of place; and our understanding of who we are. Drawing on in-depth fieldwork with commuters, journalists, transit advocates, policymakers, and others in Sydney, Australia, Transit Life takes a holistic perspective to change how we think about commuting. Rather than arguing that transport infrastructure investment alone can solve our commuting problems, Bissell explores the more subtle but powerful forms of social change that commuting creates. He examines the complex politics of urban mobility through multiple dimensions, including the competencies that commuters develop over time; commuting dispositions and the social life of the commute; the multiple temporalities of commuting; the experience of commuting spaces, from footpath to on-ramp, both physical and digital; the voices of commuting, from private rants to drive-time radio; and the interplay of materialities, ideas, advocates, and organizations in commuting infrastructures.
