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Throughout most of human history, events and phenomena of interest have been characterized using space and time as their major characteristic dimensions, in either absolute or relative conceptualizations. Space–time analysis seeks to understand when and where (and sometimes why) things occur. In the context of several of the most recent and substantial advances in individual movement data analysis (time geography in particular) and spatial panel data analysis, we focus on quantitative space–time analytics. Based on more than 700 articles (from 1949 to 2013) we obtained through a key word search on the Web of Knowledge and through the authors' personal archives, this article provides a synthetic overview about the quantitative methodology for space–time analysis. Particularly, we highlight space–time pattern revelation (e.g., various clustering metrics, path comparison indexes, space–time tests), space–time statistical models (e.g., survival analysis, latent trajectory models), and simulation methods (e.g., cellular automaton, agent-based models) as well as their empirical applications in multiple disciplines. This article systematically presents the strengths and weaknesses of a set of prevalent methods used for space–time analysis and points to the major challenges, new opportunities, and future directions of space–time analysis. [ABSTRACT FROM PUBLISHER]

Compactness of a congressional district is a traditional principle in adjudicating gerrymandering claims in political redistricting. During the last decade, many states have used compactness as an important criterion to constrain the presence of gerrymandering in the redistricting process. In this study, we conducted an array of spatiotemporal analyses aiming to evaluate the changes in compactness between the 112th and 113th Congressional districting plans in California and North Carolina, two states that have been well known for their heavy gerrymandering for years. We employed classic shape-based compactness measures, moment-of-inertia-based measures, and measures of partisan bias to assess the districting plans from multiple angles, including irregularity of district boundaries, spatial dispersion, population-weighted shape dispersion, and partisan symmetry. This new and combined use of spatial measures evidenced remarkable increases on the average compactness scores for California's Congress, suggesting general alleviation of the bipartisan gerrymandering in the previous plan. On the contrary, the partisan gerrymandering in North Carolina intensified in the current map, indicated by the substantial decline in the compactness scores for a majority of the districts. Analysis of partisan bias in the districting plans suggested a very slight bias toward Democrats in California in both districting plans. In North Carolina, the partisan advantage shifted from Democrats to Republicans during redistricting. Comparative analysis between the two families of spatial measures revealed the superiority of the moment of inertia family to the classic shape-based indexes for measuring compactness of congressional districts. [ABSTRACT FROM AUTHOR]

Against the background of increased interest in subjectively experienced well-being in economics, psychology, and the social sciences, this article analyzes how such well-being is associated with geographical context, social contacts, and life circumstances. The empirical analysis of data collected in Hong Kong is used to elaborate and support two main claims. The first is that geography matters to not only overall well-being but also momentary well-being and that researchers should be careful to specify the influence of geographical context correctly. We therefore employ an approach that is informed by various strands of time–geographical thought and find that life satisfaction is associated more strongly with geographical context than is momentary well-being. Second, we confirm positive relations between social contacts and experienced well-being but extend earlier research by showing that these relations stretch across multiple timescales and depend to some extent on the duration of an activity episode and with whom the activity episode is undertaken. This means that the use of simple indicators of social capital is inadequate for making the complex linkages between well-being and people's social contacts understandable in empirical research. [ABSTRACT FROM AUTHOR]

Time geography is a powerful framework for analyzing human activities under various space–time constraints. At the core of time geography is the concept of the space–time prism, which delimits an individual's potential activity locations in space and time. The classical space–time prism, however, admits only deterministic travel speeds and ignores the stochastic nature of travel environments. In this article, the classical space–time prism model is extended to congested road networks with travel time uncertainty. A reliable space–time prism is proposed to consider explicitly an individual's on-time arrival probability concerns in the face of travel time uncertainty. The reliable space–time prism is defined as the set of space–time locations where an individual can participate in an activity and return to his or her destination with a given on-time arrival probability. To construct such a reliable space–time prism in a road network, a solution algorithm is developed. A case study using real-world traffic information is carried out to demonstrate the applicability of the proposed prism model. The results of the case study indicate that the proposed prism model can represent well individuals’ space–time taking into account various on-time arrival probability concerns. [ABSTRACT FROM PUBLISHER]

Space–time integration has long been the topic of study and speculation in geography. However, in recent years an entirely new form of space–time integration has become possible in geographic information systems (GIS) and GIScience: real-time space–time integration and interaction. Although real-time spatiotemporal data are now being generated almost ubiquitously, and their applications in research and commerce are widespread and rapidly accelerating, the ability to continuously create and interact with fused space–time data in geography and GIScience is a recent phenomenon, made possible by the invention and development of real-time interactive (RTI) Global Positioning System (GPS)/GIS technology and functionality in the late 1980s and early 1990s. This innovation has since functioned as a core change agent in geography, cartography, GIScience, and many related fields, profoundly realigning traditional relationships and structures, expanding research horizons, and transforming the ways in which geographic data are now collected, mapped, modeled, and used, both in geography and in science and society more broadly. Real-time space–time interactive functionality remains today the underlying process generating the current explosion of fused spatiotemporal data, new geographic research initiatives, and myriad geospatial applications in governments, businesses, and society. This article addresses briefly the development of these real-time space–time functions and capabilities; their impact on geography, cartography, and GIScience; and some implications for how discovery and change can occur in geography and GIScience and how we might foster continued innovation in these fields. [ABSTRACT FROM PUBLISHER]

Space and time frame all aspects of the discipline of geography. Integration is normally interpreted by geographers as a straddling of the environmental–social divide, but a more profound interpretation stresses the issues involved in coupling environmental and social processes: a science of integration rather than an integration of sciences. Seven examples of distinct data types and scientific questions are examined, leading to the conclusion that a space–time geographic information system is unlikely to emerge in the near future. Instead, attention should focus on the systematic study of the issues involved in integration through the formal environment of a computational system. [ABSTRACT FROM PUBLISHER]

In this era of abundant space–time geographic information systems (GIS) data, one challenge in GIScience is to adapt and improve current GIS environments to facilitate new ways of space–time thinking and to fully exploit the information in these data. This article focuses on the use of spatiotemporal data transformations using the construct of a space–time cube, which is a space–time coordinate space with geographical horizontal axes and a temporal vertical axis. I have chosen three examples in which the concept of space–time cubes is applied to different themes and on different scales to illustrate how diverse subjects can be interpreted with space–time analysis and transformations of space–time data. The transformation functions, such as space–time overlays, interpolation, and surface operations, can be understood as natural extensions of popular analytical operations already present in current GIS and should be intrinsic in the next generation of GIS to handle the dense space–time information that is available to us. [ABSTRACT FROM PUBLISHER]

The space–time behavior approach has become an influential methodology in Chinese urban geography. In this article I provide an overview of space–time behavior research in China, focusing on theoretical and methodological progress as well as key themes and findings from recent empirical studies. I argue that space–time behavior research offers a new perspective for understanding the complexity and diversity of human behavior patterns during the large-scale spatial and institutional transition in Chinese cities. Yet although Chinese urban geographers have made more methodological progress in data collection and analytic tools, theoretical development still lags behind compared to the space–time behavior approach in the West. The article concludes by discussing key theoretical and practical challenges for future development of space–time activity research in China. [ABSTRACT FROM PUBLISHER]

Many fundamental notions in geographic and social science research still tend to be conceptualized largely in static spatial terms, ignoring how our understanding of the issues we study can be greatly enriched through the lenses of time and human mobility. This article revisits three such notions: racial segregation, environmental exposure, and accessibility. It argues for the need to expand our analytical focus from static residential spaces to other relevant places and times in people's everyday lives. Mobility is an essential element of people's spatiotemporal experiences, and these complex experiences cannot be fully understood by just looking at where people live. As many social scientists are interested in studying segregation, environmental exposure, and accessibility, geographers can contribute to advancing temporally integrated analysis of these issues through careful examination of people's everyday experiences as their lives unfold in space and time. Interdisciplinary research along this line could have a broad impact on many disciplines beyond geography. [ABSTRACT FROM PUBLISHER]

An introduction is presented to a special section on space-time integration in geography and GIScience (Geographic Information Science) which discusses various reports within the section on topics including global positioning system (GPS) technologies, human mobility, and time.

Climate change represents a new era in the development of capitalism, whereby humanity has become such a force of nature so as to destabilize its own environment and ultimately threaten its survival—neo-modernity. This article explores the creation of markets to control greenhouse gas emissions. Carbon markets are an important infrastructure to enable humanity to integrate nature into its sociopolitical and economic organization. The carbon markets are the embodiment of a process designed to reorganize human activities but also to organize and assimilate the natural environment. As with other eras, the key to success in neo-modernity is organizing complex and divergent human activities across space and time. Using an institutional approach, built on case studies and close dialogue with market participants and policymakers in the United States and Europe, this article analyzes the construction of carbon market infrastructure including how the markets organize environmental impacts in space and time. Particular attention is paid to the compressions of the spacetime of carbon commodities through the establishment of platforms, exchanges, and verifiers. The article concludes that markets are coordinating networks—the epitome of neo-modernity infrastructure and the beginning of a process through which the natural environment will become valued only in the context of further capitalist expansion. [ABSTRACT FROM AUTHOR]

Classic time geography is powerful but rigid, admitting only uniform travel velocities. Computational time geographic methods that resolve the uniform velocity assumption through transportation networks or isochrones only partially address this weakness and do not have a rigorous theoretical foundation. This article develops an analytical time geographic theory for the case where travel velocities vary continuously across space. Using the continuous transportation or “urban fields” tradition in quantitative geography and regional science, this article formulates analytical definitions of the space-time path and prism for the case where unobserved components are characterized by minimum cost curves through an inverse velocity field rather than straight line segments through a uniform velocity plane. This provides a geometrically and visually oriented approach to capturing complex velocities that complements existing methods. Time geographic fields also generalize time geography as the classic and isochrone versions are special cases; these now have a rigorous analytical foundation. It also can extend the network approach by treating links as regions with continuously varying velocities. Time geographic fields are also useful for nonnetwork-constrained phenomena such as movement through terrain, water, and air. This article illustrates the approach using a computational implementation based on a lattice approximation. [ABSTRACT FROM AUTHOR]

Although land changes are characterized by dimensionality in both space and time, and a multitude of methods and techniques have been developed to model them, the temporal dimension has seldom been adequately addressed by commonly used methods. In the context of temporal complexities represented in different space-time data models, this study aims to establish a framework for applying survival analysis theory and techniques to geographical land change modeling. Our efforts focus on (1) introducing basic concepts in survival analysis and their connections to space-time data commonly used in land change analysis, (2) using survival metrics to describe temporal patterns that are not easily detected by other methods, and (3) applying survival analysis methods to disclose effects of varying temporal patterns and uncertainties. Our findings suggest that survival analysis, coupled with geographic information systems (GIS) and remote sensing data, can effectively disclose relationships in land changes, and in many instances excel in shedding light on the temporal patterns of land changes. [ABSTRACT FROM AUTHOR]

Discusses geographers' perception of an appropriate image of a person. Identification of the image through various extensions; Human extensibility as a key to the processes of social structuration; Determinants of extensibility.

The portrayal of complex surfaces stemming from the gravity model in three-dimensional format can greatly facilitate an understanding of spatial behavior. Not only can the geometric properties of the gravity model be understood more readily, but such a portrayal is extremely valuable in the conduct of actual experiments. [ABSTRACT FROM AUTHOR]

A method is presented for estimating the quantitative reliability of isoline maps constructed from observations that vary in space and time. The reliability of isolines is expressed as a variance and equations are developed which relate this variance to observational errors, time errors, positional errors, synopticity errors, primary and secondary interpolation errors, and the space-time rates-of-change and the directions of the gradients of the mapped variable. Equations are also developed for designing a survey whose end product is to be an isoline map of specified variance. These relate the variance to the speeds of travel of the observers, the number of observers the dimensions of the surveyed area, and the type of survey pattern. Four types of survey patterns are illustrated: continuous observations along equi-spaced parallel transects and point observations in aligned rectangular, aligned triangular, and unaligned rectangular patterns.