This article presents the dramatic growth in the use of advanced tracking technologies such as Global Positioning Systems (GPS) and advanced mobile phones—known as smartphones—for academic research in the last decade, with an emphasis on geography and urban planning. Tracking technologies supply researchers and planners with continuous high resolution data in time (up to seconds) and space (up to few meters); this opens up new possibilities for basic research and applicative implementations that can assist academics, urban planners, transportation planners and other stakeholders. The fast penetration of smartphones in recent years will have a significant impact on the way we will implement tracking technologies in the future. We discuss how these devices can be employed in research, tracking individuals in time and space and functioning as location-aware survey tools in real time, among other things. We also engage in a debate over the advantages, disadvantages, and limitations of smartphones in this context, and highlight new research trends that are beginning to appear following the introduction of smartphones.

Accessibility, particularly for users of public transport, is an important consideration in sustainable mobility policies. Various accessibility measures have been suggested in the literature, most at coarse aggregate spatial resolutions of zones or neighborhoods. Based on recently available urban GIS, we suggest that accessibility can and should be measured from the viewpoint of a human being traversing the transportation network from one building as origin to another at the destination. We estimate transport accessibility by car and by public transport based on mode-specific travel times and corresponding paths, including walking and waiting, at the resolution of individual buildings. Our application utilizes graph databases and parallel computing to allow fast construction of high-resolution accessibility maps for an entire metropolitan area with its 100-1000K buildings. The application is tested and applied in a case study involving the evaluation of the 2011 bus line reform in the city of Tel-Aviv. Specifically, we demonstrate that the reform increased both the average accessibility for the entire city and had a minor impact on its equity mainly attributed to longer trips. Still the reform increased accessibility, mainly to origins which previously had lower accessibility levels. The results further show essential dependence of accessibility estimates on spatial resolution - unless spatially explicit representation of the trip is enabled, biased estimates can arise. The new approach and fast computational method can be employed for investigating the distributional effects of transportation infrastructure investments and, further, for interactive planning and agent-based simulation of the urban transport network.

This paper illustrates how synthetic big data can be generated in order to meet the planning challenges of urban recovery in the aftermath of a disaster. Small areal statistical units are decomposed into households and individuals using a GIS buildings data layer. Households and individuals are then profiled with socio-economic attributes and combined with an agent based simulation model in order to create dynamics. The resultant data is 'big' in terms of volume, variety and versatility. It allows for different layers of spatial information to be populated and embellished with synthetic attributes. The data decomposition process involves moving from a database describing only hundreds or thousands of spatial units to one containing records of millions of buildings and individuals over time. The method is illustrated in the context of a hypothetical earthquake in downtown Jerusalem. Agents interact with each other and their built environment. Buildings are characterized in terms of land-use, floorspace and value. Agents are characterized in terms of income and sociodemographic attributes and are allocated to buildings. Simple behavioral rules and a dynamic house pricing system inform residential location preferences and land use change, yielding a detailed account of urban spatial and temporal dynamics. These techniques allow for the bottomup formulation of the behavior of an entire urban system. Outputs relate to land use change, change in capital stock and socio-economic vulnerability. Delivering the data to planners and the informed public is facilitated through a dedicated dynamic mapping web site.

In this paper we use cellular network data to examine spatial activity. So far, the majority of data on spatial activity such as commuting and travel for leisure and shopping purposes were based on census and/or survey data. Normally, data was based on a limited number of participants and the time interval between data collection and its release for research resulted in a time gap between actual identification of a phenomenon and its analysis. Using data stored in smartphones is of great potential for research and application in the planning discipline. In this paper we use data obtained from a start-up company that monitors the activity of cellular network data in Israel. This type of big data enables the identification of place-of-residence and activity patterns of smartphone users. By focusing on the metropolitan CBD of Tel Aviv, we analyze the spatial activity of visitors and provide empirical evidence for wellrecognized but ill-documented processes.

In this paper we use cellular network data to examine spatial activity. So far, the majority of data on spatial activity such as commuting and travel for leisure and shopping purposes were based on census and/or survey data. Normally, data was based on a limited number of participants and the time interval between data collection and its release for research resulted in a time gap between actual identification of a phenomenon and its analysis. Using data stored in smartphones is of great potential for research and application in the planning discipline. In this paper we use data obtained from a start-up company that monitors the activity of cellular network data in Israel. This type of big data enables the identification of place-of-residence and activity patterns of smartphone users. By focusing on the metropolitan CBD of Tel Aviv, we analyze the spatial activity of visitors and provide empirical evidence for wellrecognized but ill-documented processes.

The population dispersal plan that was prepared by the Interministerial Committee in 1963 proposed focusing efforts on the urban population. It presented a policy for strengthening the development towns, especially the distant ones. The Committee's report shows awareness of the resource constraints on agricultural settlement development, and recognition that too many urban settlements, which were also too small, were founded in peripheral areas during the 1950s. The Committee proposed concentrating on reinforcing the existing cities in the years to1970, increasing their residents to reach their target populations of 10,000 as soon as possible, and advised against establishing any new towns until the existing cities reach their minimum target populations.