Space–time interaction of residential burglaries in Wuhan,China

Borrowing methods from epidemiology, studies of spatiotemporal regularities of crime have been booming in various industrialized countries. However, few such attempts are empirical studies using crime data in developing countries due to a lack of data availability. Utilizing a recent burglary dataset in Wuhan, the fourth largest city in China, current research applied the sequential kernel density estimation and the space–time K-function methods to analyze the spatiotemporal changes of hotspots of residential burglaries. The results show that, both spatial and spatiotemporal clustering exists. The hotspots were relatively stable over time. The space–time clustering, however, shows significant concentrations both in space and over time. In addition, analytic results show significant effects of distance decay in terms of occurrences of burglary incidents along the spatial and temporal dimensions. Moreover, findings from the research provide critical information on the space–time rhythm of crime, and therefore can be utilized in crime prevention practice. Finally, the implications of the findings and limitations are discussed.     

Urban Pulse—(RE)Making Space for Globalization in Istanbul

This paper provides critical reflections on the urban transformation campaign launched by the Istanbul Metropolitan Municipality (IMM) as part and parcel of its ambitions to upgrade Istanbul to "world city" status. I focus on two main aspects of "urban transformation" in Istanbul: prestige mega-projects and (re)development of informal housing areas, with particular emphasis on the latter. I examine how poor residents' livelihoods are put at stake in spite of the IMM's claim that "urban transformation" is ultimately beneficial for all citizens. I conclude with the unique policy challenges that the local governments face in developing participatory models for urban renewal and regeneration in Istanbul.     

Early Detection of Terrorism Outbreaks Using Prospective Space–Time Scan Statistics

Terrorism is a complex phenomenon with high uncertainty involving a myriad of dynamic known and unknown factors. It is and will remain a challenge to predict or detect terrorism outbreaks at an early stage. This research presents an alternative approach for modeling terrorism activity, one that monitors and detects space–time clusters of terrorist incidents using prospective space–time scan statistics. Such clusters provide indicators of potential outbreaks of terrorist incidents. To evaluate the effectiveness of the approach, we analyze the terrorist incidents in the Consortium for the Study of Terrorism and Responses to Terrorism's (START) Global Terrorism Database (GTD) from 1998 to 2004. Clusters of terrorist events are detected at each time stamp and life trajectories of these clusters are constructed based on their space–time relationship to each other. Through the life trajectories and trends of clusters, we demonstrate how space–time scan statistics detect terrorism outbreaks at an early stage.     

Space–time multiple regression model for grid-based population estimation in urban areas

We can collect, store, and analyze a huge amount of information about human mobility and social interaction activities due to the emergence of information and communication technologies and location-enabled mobile devices under cyber physical system frameworks. The high spatial resolution of population data on a multi-temporal scale is required by transport planners, human geographers, social scientists, and emergency management teams. In this study, we build a space-time multiple regression model to estimate grid-based (500 m × 500 m) spatial resolution at multi-temporal scale (30-min intervals) population data based on the space-time relationship among geospatially enabled person trip (PT) survey data and incorporate both mobile call (MC) and geotagged Twitter (GT) data. Since using geospatially enabled PT survey data as dependent variables enables us to acquire actual population amounts, which strongly depend on MCs and social interaction activities. Although many grids have a strong correlation between PT and MC/GT, some show fewer correlation results, especially where the grids have factories, schools, and workshops in which fewer MCs are found but a large population is presented. Although GT data are sparser than MCs, people from amusement and tourist areas can be detected by GT data. The space-time multiple regression model can also estimate the different amounts of populations based on human travel behavior that changes over space and time. According to accuracy assessments, the night-time estimated results, especially between 00:00 and 06:30, strongly correlate with national census data except in places where the grids have railway and subway stations.     

Space–time opportunities for multiple agents: a constraint‐based approach

Constraint‐based models and models constructing accessibility measures mainly focus on single agents having only one available transport mode. However, numerous cases exist where multiple agents or groups of individuals with different available transport modes want to participate in a joint activity at a certain location. The aim of this paper is to provide new insights into representing and reasoning about feasible space–time opportunities for multiple agents. Relying on concepts of time geography, we propose a conceptual framework in order to determine interaction spaces for groups of individuals. Besides availability of means of transport and the locations of each individual, minimum activity duration and opening hours of opportunities are taken into account. The reasoning about space and time is visualized in three dimensions using a hybrid (CAD/GIS) system.     

Weighting the Effects of Spatial Cognition and Activity Anchors on Time–Space Activity

Many elements are known to affect the decision-making procedures that underlie time–space activity patterns. Yet, knowledge regarding the relations between these elements is lacking. In this article, a hierarchical structure of external and cognitive time–space behavioral influences is proposed based on the results of a field experiment. The experiment relied on an in situ sampling of stated and overt behaviors of visitors to a touristic site in northern Israel, using questionnaires and Global Positioning System loggers. Two experimental treatments were simultaneously applied during sampling, dividing the sample into four groups: Each participant received on entry one of two maps, designed according to different cartographical–cognitive approaches; new activity stations were placed during half of the sampling days, meaning that each participant was exposed to one of two possible spatial layouts. The behavioral patterns recorded expose each treatment's distinct behavioral effect along with its relative weight within the decision-making process, thus pointing toward a hierarchical structure.     

Space–time prism bounds of activity programs: a goal-directed search in multi-state supernetworks

Space–time prism (STP), which envelops the spatial and temporal opportunities for travel and activity participation within a time frame, is a fundamental concept in time geography. Despite many variants, STPs have been mostly modeled for one flexible activity between two anchor points. This study proposes a systemic approach to construct the STP bounds of activity programs that usually include various possible realizations of activity chains. To that effect, multi-state supernetworks are applied to represent the relevant path sets of multi-activity travel patterns. A goal-directed search method in multi-state supernetworks is developed to delineate the potential space–time path areas satisfying the space–time constraints. Particularly, the approximate lower and upper STP bounds are obtained by manipulating the goal-directed search procedure utilizing landmark-based triangular inequalities and spatial characteristics. The suggested approach can in an efficient fashion find the activity state dependent bounds of STP and potential path area. The formalism of goal-directed search through multi-state supernetworks addresses the fundamental shift from constructing STPs for single flexible activities to activity programs of flexible activity chains.     

A Review of “Breathing Space: How Allergies Shape Our Lives and Landscapes”

This paper expands the human capital model to compare the migration propensities of Cubans, Mexicans, and Puerto Ricans within the U.S. between 1985 and 1990. Using the 5% PUMS from the 1990 U.S. Census, both aggregate migration streams and micro-level migration propensities are estimated for Cubans, Mexicans, and Puerto Ricans. The effects of personal factors, the economic environment, and the presence of fellow nationals are examined in the context of larger geographic patterns, and discussed in terms of each nationality's immigration history and cultural context.

While many factors effect migration behavior similarly, there are notable differences in the way education, English fluency, and unemployment rate affect migration propensity of the native-born and foreign-born of each nationality. Differences are also apparent at the macro-level. Puerto Ricans show signs of dispersing out of New York; Mexicans are redistributing within the Southwest; and Cubans are re-concentrating in Florida. Both levels of analysis point to how immigration history, settlement patterns, and cultural context influence migration behavior. The results demonstrate the benefits of using an expanded human capital approach to explain migration differences, and highlight the diversity of population redistribution occurring within Hispanic nationalities.     

A Review of: “Loose Space: Possibility and Diversity in Urban Life”

Basso, Keith H. Wisdom Sits in Places: Language and Landscape among the Western Apache

Foote, Kenneth E. Shadowed Ground: America's Landscapes of Violence and Tragedy

Harries, Keith and Cheatwood, Derral The Geography of Execution: The Capital Punishment Quagmire in America

Larkham, Peter J. Conservation and the City

James, Preston E. and Martin, Geoffrey J. All Possible Worlds: A History of Geographical Ideas

Meir, Avinoam As Nomadism Ends: The Israeli Bedouin of the Negev

Ruddick, Susan M. Young and Homeless in Hollywood: Mapping Social Identities

Smith, Neil The New Urban Frontier: Gentrification and the Revanchist City     

Dynamic Prediction Model of Overburden Settlement in Deep Mining Areas based on Space–Time Relationship

Natural Resources Research - Depletion of shallow mineral resources caused by deep mining has become an inevitable trend, and deep mining can increase safety accidents and geological hazards....     

Geospatial Analysis of Space–Time Patterning of ENSO Forced Daily Precipitation Distributions in the Gulf of Mexico

The Gulf of Mexico experiences significant changes in the distribution of daily precipitation totals that are linked to the El Niño–Southern Oscillation (ENSO). This research uses geospatial techniques to examine distribution patterns of ENSO-related precipitation. Kolmogorov–Smirnov test results comparing daily rainfall distributions for El Niño and La Niña are mapped at a 1° × 1° latitude/longitude resolution, and hotspot analysis using local Moran's I is performed to identify spatial clustering. Results indicate that ENSO-forced spatial and temporal variation in daily precipitation distributions influence large areas of the Gulf of Mexico region from August through January.     

Measuring Space–Time Access to Food Retailers: A Case of Temporal Access Disparity in Franklin County,Ohio

Typical measures of food access use spatial-only methods to identify nearby food outlets and the quantity, quality, and variety of food available. This measure of spatial access falls short in explaining the effect that the operating hours of food retailers have on food access. Our study aims to complement the spatial dimension of access measures by bringing time in as a new constraint on food access. To this end, we developed three measures of spatial, temporal, and spatiotemporal access and correlated these measures with socioeconomic status (SES) in a case in Columbus, Ohio. Findings from our analysis of food access disparity suggest that low-SES neighborhoods in Columbus are not at a disadvantage of spatial access, but their limited temporal access is a more pressing concern. Implications drawn from the study would assist community advocates, local governments, and other stakeholders in deriving a better understanding of the local foodscape that are not only mediated by space but also time.     

Analyzing Accessibility Using Parcel Data: Is There Still an Access–Space Trade-Off in Long Beach,California?

This article analyzes the impact of changing housing and neighborhood characteristics on the accessibility of neighborhood businesses using Long Beach, California, as a case study. Although advocates of smart growth and New Urbanism encourage land use mixing, aggregate-level analysis can be too coarse to pick up on fine-grained aspects of urban streetscapes. This study uses assessor parcel records and a point-based business establishment data set to analyze city-wide patterns of accessibility from individual dwelling units to thirty-one types of neighborhood businesses, including grocery stores, service shops, drug stores, doctor's offices, and banks. Regression results compare parcel-level and neighborhood-level drivers of accessibility between 2006 and 2015 to gauge the aggregated effect of recent economic, demographic, and built environment changes on this aspect of urban spatial structure. Larger homes in older, multiunit buildings and higher income neighborhoods show substantial increases in accessibility to most establishment types, suggesting a trend toward both greater accessibility and larger dwelling units—despite the traditional trade-off between access and space. Although gradual increases in home and business density increased overall accessibility over this period, weaker neighborhood-level results indicate that this trend is less pronounced in high-poverty and non-white areas.     

Path Dependency and Patterns of Collective Action: Space,Place, and Agency in Long Beach,California, 1900–1960

Drawing on the insights of the geography, structural, and social movement literature this study analyzes the interactive effects of structure, space, place, and agency on patterns of collective action in Long Beach, California. Long Beach and Los Angeles occupy the same regional landscape with similar economies, yet the logic of collective action varies considerably. It is argued that preceding 1960, pro-business elites in Long Beach allied with their Los Angeles counterparts to spatially restrict labor organizing and foster patterns of noncontiguous interdependencies within and among labor and community groups. Through violence, cultural references, local and extralocal political policies, and regional coalition building before 1960, the Long Beach ruling elites fragmented the labor and community sector and inhibited the emergence of an organizational infrastructure necessary to foster community-based change after 1960. The legacies of this period are reflected in a fragmented labor and community sector set against a powerful ideologically driven, business-led opposition.