Urban metabolism - WikipediaUrban metabolism is a model to facilitate the description and analysis of the flows of the materials and energy within cities, such as undertaken in a material flow analysis of a city. It provides researchers with a metaphorical framework to study the interactions of natural and human systems in specific regions. From the beginning, researchers have tweaked and altered the parameters of the urban metabolism model. C. Kennedy and fellow researchers have produced a clear definition in the 2007 paper The Changing Metabolism of Cities claiming that urban metabolism is "the sum total of the technical and socio-economic process that occur in cities, resulting in growth, production of energy and elimination of waste. With the growing concern of climate change and atmospheric degradation, the use of the urban metabolism model has become a key element in determining and maintaining levels of sustainability and health in cities around the world. Urban metabolism provides a unified or holistic viewpoint to encompass all of the activities of a city in a single model.
Urban Computing FoundationThe Urban Computing Foundation is a neutral forum for accelerating open source and community development that improves mobility, safety, road infrastructure, traffic congestion and energy consumption in connected cities.
Urban InformaticsThis open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning.Wenzhong Shi, Michael F. Goodchild, Michael Batty, Mei-Po Kwan, Anshu Zhang
Urban human mobility data mining: An overviewUnderstanding urban human mobility is crucial for epidemic control, urban planning, traffic forecasting systems and, more recently, various mobile and network applications. Nowadays, a variety of urban human mobility data have been gathered and published. Pervasive GPS data can be collected by mobile phones. A mobile operator can track people’s movement in cities based on their cellular network location. This urban human mobility data contains rich knowledge about locations and can help in addressing many urban challenges such as traffic congestion or air pollution problems. In this article, we survey recent literature on urban human mobility from a data mining view: from the data collection and cleaning, to the mobility models and the applications. First, we summarize recent public urban human mobility data sets and how to clean and preprocess such data. Second, we describe recent urban human mobility models and predictors, e.g., the deep learning predictor, for predicting urban human mobility. Third, we describe how to evaluate the models and predictors. We conclude by considering how applications can utilize the mobility models and predictive tools for addressing city challenges.Kai Zhao, Sasu Tarkoma, Siyuan Liu and Huy Vo