Learn More
Title Type cities and complexity understanding cities with cellular automata agent-based models and fractals PDF the complexity of cooperation agent-based models of competition and collaboration PDF party competition an agent-based model princeton studies in complexity PDF sharing cities a case for truly smart and sustainable cities urban and industrial(More)
Mashups, composed of mixing different types of software and data, first appeared in 2004 and 'map mashups' quickly became the most popular forms of this software blending. This heralded a new kind of geography called 'Neogeography' in which non-expert users were able to exploit the power of maps without requiring the expertise traditionally associated, in(More)
We propose and test a model that describes the morphology of cities, the scaling of the urban perimeter of individual cities, and the area distribution of systems of cities. The model is also consistent with observable urban growth dynamics, our results agreeing both qualitatively and quantitatively with urban data. The resulting growth morphology can be(More)
In this article, we explore the concepts and applications of Web 2.0 through the new media of NeoGeography and its impact on how we collect, interact and search for spatial information. We argue that location and space are becoming increasingly important in the information technology revolution. To this end, we present a series of software tools which we(More)
Despite a century of effort, our understanding of how cities evolve is still woefully inadequate. Recent research, however, suggests that cities are complex systems that mainly grow from the bottom up, their size and shape following well-defined scaling laws that result from intense competition for space. An integrated theory of how cities evolve, linking(More)
Agent-based modelling (ABM) is becoming the dominant paradigm in social simulation due primarily to a worldview that suggests that complex systems emerge from the bottom-up, are highly decentralised, and are composed of a multitude of heterogeneous objects called agents. These agents act with some purpose and their interaction, usually through time and(More)
An important issue in the study of cities is defining a metropolitan area, because different definitions affect conclusions regarding the statistical distribution of urban activity. A commonly employed method of defining a metropolitan area is the Metropolitan Statistical Areas (MSAs), based on rules attempting to capture the notion of city as a functional(More)