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.     

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.     

Living austerity urbanism: space–time expansion and deepening socio-spatial inequalities for disadvantaged urban youth in Ireland

After the 2008 financial crisis, Ireland implemented a severe austerity program which drastically reshaped the opportunities and constraints experienced by youth living in disadvantaged urban neighborhoods. Rising unemployment, reduced social welfare, and funding cuts for support organizations limited the opportunities of urban life for disadvantaged youth. This article uses the experience of austerity urbanism of young adults from Ballymun (Dublin) and Knocknaheeny (Cork), both among the most disadvantaged neighborhoods of their cities, to argue that austerity, through time-space expansion, removes services, facilities and opportunities from deprived urban neighborhoods, thus reinforcing and intensifying socio-spatial inequalities. In an effort to bring State finances under control and to revitalize the economy the whole urban fabric, and the urban population, is managed for the purpose of economic recovery. Urban life becomes restricted as disadvantaged urban youth becomes socially and spatially excluded from vital urban opportunities and amenities.     

An analytic solution to the alibi query in the space–time prisms model for moving object data

Moving objects produce trajectories, which are stored in databases by means of finite samples of time-stamped locations. When speed limitations in these sample points are also known, space–time prisms (also called beads) (Pfoser and Jensen 1999 Pfoser, D. and Jensen, C.S. 1999. “Capturing the uncertainty of moving-object representations”. In Advances in spatial databases (SSD’99), Hong Kong, China, July 20–23, 1999, Vol. 1651, 111–132. Lecture notes in Computer Science.  [Google Scholar], Egenhofer 2003 Egenhofer, M. 2003. “Approximation of geopatial lifelines”. In SpadaGIS, workshop on spatial data and geographic information systsems, 4SpaDaGIS–Workshop on Spatial Data and Geographic Information Systems, Milano, Italy, March 2003. University of Genova.  [Google Scholar], Miller 2005 Miller, H. 2005. A measurement theory for time geography. Geographical Analysis, 37(1): 17–45. [Crossref], [Web of Science ®] , [Google Scholar]) can be used to model the uncertainty about an object's location in between sample points. In this setting, a query of particular interest that has been studied in the literature of geographic information systems (GIS) is the alibi query. This boolean query asks whether two moving objects could have physically met. This adds up to deciding whether the chains of space–time prisms (also called necklaces of beads) of these objects intersect. This problem can be reduced to deciding whether two space–time prisms intersect.

The alibi query can be seen as a constraint database query. In the constraint database model, spatial and spatiotemporal data are stored by boolean combinations of polynomial equalities and inequalities over the real numbers. The relational calculus augmented with polynomial constraints is the standard first-order query language for constraint databases and the alibi query can be expressed in it. The evaluation of the alibi query in the constraint database model relies on the elimination of a block of three exªistential quantifiers. Implementations of general purpose elimination algorithms, such as those provided by QEPCAD, Redlog, and Mathematica, are, for practical purposes, too slow in answering the alibi query for two specific space–time prisms. These software packages completely fail to answer the alibi query in the parametric case (i.e., when it is formulated in terms of parameters representing the sample points and speed constraints).

The main contribution of this article is an analytical solution to the parametric alibi query, which can be used to answer the alibi query on two specific space–time prisms in constant time (a matter of milliseconds in our implementation). It solves the alibi query for chains of space–time prisms in time proportional to the sum of the lengths of the chains. To back this claim up, we implemented our method in Mathematica alongside the traditional quantifier elimination method. The solutions we propose are based on the geometric argumentation and they illustrate the fact that some practical problems require creative solutions, where at least in theory, existing systems could provide a solution.     

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.     

Calibrating a neural network‐based urban change model for two metropolitan areas of the Upper Midwest of the United States

We parameterized neural net‐based models for the Detroit and Twin Cities metropolitan areas in the US and attempted to test whether they were transferable across both metropolitan areas. Three different types of models were developed. First, we trained and tested the neural nets within each region and compared them against observed change. Second, we used the training weights from one area and applied them to the other. Third, we selected a small subset (～1%) of the Twin Cities area where a lot of urban change occurred. Four model performance metrics are reported: (1) Kappa; (2) the scale which correct and paired omission/commission errors exceed 50%; (3) landscape pattern metrics; and (4) percentage of cells in agreement between model simulations. We found that the neural net model in most cases performed well on pattern but not location using Kappa. The model performed well only in one case where the neural net weights from one area were used to simulate the other. We suggest that landscape metrics are good to judge model performance of land use change models but that Kappa might not be reliable for situations where a small percentage of urban areas change.     

Quantitative estimation and spatial reconstruction of urban and rural construction land in Jiangsu Province, 1820–1985

Land cover is the most evident landscape signal to characterize the influence of human activities on terrestrial ecosystems. Since the industrial revolution, the expansion of construction land has profoundly changed the status of land use coverage and changes. This study is proposed to reconstruct the spatial pattern of construction land (urban construction land and rural settlement land) for five historical periods over the past 200 years in Jiangsu Province with 200 m × 200 m grids on the basis of quantitative estimation. Urban construction land is estimated based on data about city walls, four gates along walls, and other socio-economic factors. Rural settlement land is calculated based on the rural population and per capita housing allowance. The spatial pattern of historical construction land is simulated based on the distribution of modern construction land in 1985 with a quantitative-boundarysuitability control method and thorough consideration over connectivity of different land use types. The study concludes that: (1) the amount of construction land in Jiangsu Province is estimated at 963.46 km² in 1820, 1043.46 km² in 1911, 1672.40 km² in 1936, 1980.34 km² in 1952 and 10,687.20 km² in 1985; and (2) the spatial distribution of construction land features the great proclivity to water bodies and main roads and the strong polarization of existent residence. The results are verified directly and indirectly by applying the trend verification of construction land changes and patterns, the correlation analysis between rural settlement land and local arable land, and quantitative accuracy test of the reconstructed construction land to actual historical survey maps covering four sample regions in 1936.     

Effects of rural–urban migration on vegetation greenness in fragile areas: A case study of Inner Mongolia in China

Different government departments and researchers have paid considerable attention at various levels to improving the eco-environment in ecologically fragile areas. Over the past decade, large numbers of people have emigrated from rural areas as a result of the rapid urbanization in Chinese society. The question then remains: to what extent does this migration affect the regional vegetation greenness in the areas that people have moved from? Based on normalized difference vegetation index (NDVI) data with a resolution of 1 km, as well as meteorological data and socio-economic data from 2000 to 2010 in Inner Mongolia, the spatio-temporal variation of vegetation greenness in the study area was analyzed via trend analysis and significance test methods. The contributions of human activities and natural factors to the variation of vegetation conditions during this period were also quantitatively tested and verified, using a multi-regression analysis method. We found that: (1) the vegetation greenness of the study area increased by 10.1% during 2000-2010. More than 28% of the vegetation greenness increased significantly, and only about 2% decreased evidently during the study period. (2) The area with significant degradation showed a banded distribution at the northern edge of the agro-pastoral ecotone in central Inner Mongolia. This indicates that the eco-environment is still fragile in this area, which should be paid close attention. The area where vegetation greenness significantly improved showed a concentrated distribution in the southeast and west of Inner Mongolia. (3) The effect of agricultural labor on vegetation greenness exceeded those due to natural factors (i.e. precipitation and temperature). The emigration of agricultural labor improved the regional vegetation greenness significantly.     

Choice set formation with multiple flexible activities under space–time constraints

In classical time geography, an individual travel path is composed of a chain of visits, with each visit being a flexible activity between two fixed activities at two known stations. In reality, individuals tend to carry out trips with much variation and complexity, with multipurpose trips being a prominent and pervasive phenomenon. There is limited research to date on multipurpose trips in time-geographic analysis by geographic information system (GIS) scientists, or more specifically, multiple flexible activities between two fixed stations. To fill this gap, this article proposes four models for identifying the choice set with multiple flexible activities under space–time constraints. The models are derived through set-theoretic formalism based on the concept of trip chaining. The structure of the four models establishes a theoretical framework for conceptualizing trip-chaining behaviour with respect to the fixity of activities and the number of fixed stations as destinations or origins. They provide fundamental and rigorous apparatus for studying complex individual activity–travel patterns in many applied contexts when multipurpose trips are involved. This article also describes implementation of the models with a real transportation network as a way of validation.     

Road network detection from SPOT imagery for updating geographical information systems in the rural–urban fringe

Abstract

Visual interpretation of high-resolution satellite data has been useful for mapping linear features, such as roads and updating land-use changes. However, it would be beneficial to map new road networks digitally from satellite data to update digital databases using semi-automated techniques. In this paper, an algorithm called Gradient Direction Profile Analysis (GDPA) is used to extract road networks digitally from SPOT High Resolution Visible (HRV) panchromatic data. The roads generated are compared with a visual interpretation of the SPOT HRV multispectral and panchromatic data. The technique is most effective in areas where road development is relatively recent. This is due to the spectral consistency of new road networks. As new road networks are those of most interest to the land manager, this is a useful technique for updating digital road network files within a geographical information system of urban areas.     

Exploring space–time paths in physical and social closeness spaces: a space–time GIS approach

Exploring the evolution of people’s social interactions along with their changing physical locations can help to achieve a better understanding of the processes that generate the relationships between physical distance and social interactions, which can benefit broad fields of study related to social networks. However, few studies have examined the evolving relationships between physical movements and social closeness evolution. This is partially related to the shortage of longitudinal data in both physical locations and social interactions and the lack of an exploratory analysis environment capable of effectively investigating such a process over space and time. With the increasing availability of sociospatiotemporal data in recent years, it is now feasible to examine the relationships between physical separation and social interactions at the individual level in a space–time context. This research was intended to offer a spatiotemporal exploratory analysis approach to address this challenge. The first step was to propose the concept of a social closeness space–time path, which is an extension of the space–time path concept in time geography, to represent evolving human relationships in a social closeness space. A space–time geographical information system (GIS) prototype was then designed to support the representation and analysis of space–time paths in both physical and social closeness spaces. Finally, the effectiveness of the proposed concept and design in gaining insight into the impact of physical migration on online social closeness was demonstrated through an empirical study. The contributions of this study include an extension of the time–geographic framework from physical space to social closeness space, the development of a multirepresentation approach in a GIS to integrate an individual’s space–time paths in both physical and social closeness spaces, and an exploratory analysis of the evolving relationships between physical separation and social closeness over time.     

Everyday space–time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin,Paris, and Tallinn

This paper proposes a methodology for using mobile telephone-based sensor data for detecting spatial and temporal differences in everyday activities in cities. Mobile telephone-based sensor data has great applicability in developing urban monitoring tools and smart city solutions. The paper outlines methods for delineating indicator points of temporal events referenced as ‘midnight’, ‘morning start’, ‘midday’, and ‘duration of day’, which represent the mobile telephone usage of residents (what we call social time) rather than solar or standard time. Density maps by time quartiles were also utilized to test the versatility of this methodology and to analyze the spatial differences in cities. The methodology was tested with data from cities of Harbin (China), Paris (France), and Tallinn (Estonia). Results show that the developed methods have potential for measuring the distribution of temporal activities in cities and monitoring urban changes with georeferenced mobile phone data.     

A network Kernel Density Estimation for linear features in space–time analysis of big trace data

ABSTRACT

Kernel Density Estimation (KDE) is an important approach to analyse spatial distribution of point features and linear features over 2-D planar space. Some network-based KDE methods have been developed in recent years, which focus on estimating density distribution of point events over 1-D network space. However, the existing KDE methods are not appropriate for analysing the distribution characteristics of certain kind of features or events, such as traffic jams, queue at intersections and taxi carrying passenger events. These events occur and distribute in 1-D road network space, and present a continuous linear distribution along network. This paper presents a novel Network Kernel Density Estimation method for Linear features (NKDE-L) to analyse the space–time distribution characteristics of linear features over 1-D network space. We first analyse the density distribution of each linear feature along networks, then estimate the density distribution for the whole network space in terms of the network distance and network topology. In the case study, we apply the NKDE-L to analyse the space–time dynamics of taxis’ pick-up events, with real road network and taxi trace data in Wuhan. Taxis’ pick-up events are defined and extracted as linear events (LE) in this paper. We first conduct a space–time statistics of pick-up LE in different temporal granularities. Then we analyse the space–time density distribution of the pick-up events in the road network using the NKDE-L, and uncover some dynamic patterns of people’s activities and traffic condition. In addition, we compare the NKDE-L with quadrat method and planar KDE. The comparison results prove the advantages of the NKDE-L in analysing spatial distribution patterns of linear features in network space.     

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.     

Digital photogrammetry for air-photo-based construction of a digital elevation model over snow-covered areas ‐ Blamannsisen,Norway

Digital elevation models (DEMs) have been constructed over snow-covered and glaciated areas from 11 air photos optimized during production using a semi-automatic contrast-adjusting method called dodging. Construction of the DEMs from the air photos was accomplished using IMAGINE OrthoMAX software. In general, the results of the DEM construction are promising. Analytical and visual comparisons of GPS field data and published maps with the constructed DEMs indicate a high degree of agreement, with an average difference better than 2.8 m for most of the area. Errors and spurious data cells appear to have been minimized throughout most of the DEMs. One height anomaly, an erroneous peak with a height of between c. 250 m and 1200 m above the actual elevation, persistently appeared in one of the DEMs, despite numerous attempts to address the issue. Enhancements during the air-photo scanning process, such as sharpening and applying a tone curve, have been found to have a beneficial effect in reducing such erroneous results.     

A cellular automata model for simulating the evolution of positive–negative terrains in a small loess watershed

Cellular automata (CA) have been used increasingly to simulate complex geographical phenomena. This paper proposes a CA model for simulating the evolution of dynamic positive and negative (P–N) terrains in a small loess watershed. The CA model involves a large number of attributes, including the state of P–N terrains, distance to the shoulder-line, neighbourhood condition and topographic factors. Topographic factors include the slope gradient, aspect, slope length, slope variation, aspect variation, plan curvature, profile curvature, relief amplitude and flow accumulation. The CA model was applied to simulate the evolution of P–N terrains in an indoor, small loess watershed under artificial rainfall. The transition rules for CA were constructed automatically using a decision-tree algorithm. The derived transition rules are explicit for decision-makers and helpful for generating more reliable terrains. The simulation produces encouraging results in terms of numeric accuracy and spatial distribution, in agreement with natural P–N terrains. The iterative processes show that loess negative terrains continuously erode positive terrains. The development of a loess sinkhole near the centre gully head was reproduced as well, which shows the function of loess sinkholes in the formation of loess channel systems.     

Predicting the expansion of an urban boundary using spatial logistic regression and hybrid raster–vector routines with remote sensing and GIS

This paper presents an urban growth boundary model (UGBM) which utilizes spatial logistic regression (SLR), remote sensing, and GIS to simulate the differentially expanding geometry of a dynamic urban boundary over decadal time periods. SLR is used as the core algorithm in a UGBM quantifying how biophysical factors influence the rate at which all edges of an urban boundary expand over time. Spatial drivers selected from a raster-based environment are used as input predictor variables to the SLR UGBM, the output response variable being the distance between time-separated urban boundary intersections along arcs extending radially from a point centered at the urban core relative to the maximum distance. Percent area match (PAM) quantity and location goodness-of-fit metrics, fit of the predicted distance versus observed distance, and the sensitivity of the SLR UGBM to the contribution of each predictor variable are used to assess the agreement between predicted and observed urban boundaries. The model is built, tested, and validated using satellite images of the city of Las Vegas, United States of America, collected in 1990, 2000, and 2010. We compare urban boundary simulation of full and reduced SLR UGBMs to a null UGBM lacking in specificity of predictor variables. Results indicate that the SLR UGBM has a better goodness of fit compared to a null UGBM using PAM quantity and location goodness-of-fit metrics. Then, we use the SLR UGBM to predict urban boundary expansion between the years 2000 and 2010 and describe how this model can be used to plan ahead for future boundary expansions given what is known about current edge conditions.     

Bargaining for nature: treating the environment in China’s urban planning practice

ABSTRACT

In much of the contemporary academic inquiry and political discourse on Chinese cities, urban entrepreneurialism and environmentalism often appear to be analyzed disjointedly and unreflectively. They are portrayed as two conflicting interests. Commentators also view urban planners as a homogenous group of professionals and/or state agents being forced to give up environmental goals to pursue economic value of space. Using the case of Tianjin Eco-City planning, this article interrogates the bargaining process between the “ecological value” and “commodity narrative”. It offers three major arguments. First, even though the discourse of environmental sustainability has been used to legitimize economic transformation, ecological demands are creating new pressures on entrepreneurial urban governance. Second, rather than treating Chinese planners as a fully constituted, internally coherent, organizationally-fixed, and operationally-consistent group, they should be viewed as hybrid, and diverse entities that represent divergent and sometimes contentious state interests. Third, planners, though still under tremendous pressure from landed interests, can become active players to positively influence urban transformation toward more environmental care.