Geospatial Computing: Architectures and Algorithms for Mapping Applications

Beginning with the MapTube website (1), which was launched in 2007 for crowd-sourcing maps, this project investigates approaches to exploratory Geographic Information Systems (GIS) using web-based mapping, or ‘web GIS’. Users can log in to upload their own maps and overlay different layers of GIS data sets. This work looks into the theory behind how web-based mapping systems function and whether their performance can be modelled and predicted. One of the important questions when dealing with different geospatial data sets is how they relate to one another. Internet data stores provide another source of information, which can be exploited if more generic geospatial data mining techniques are developed. The identification of similarities between thousands of maps is a GIS technique that can give structure to the overall fabric of the data, once the problems of scalability and comparisons between different geographies are solved. After running MapTube for nine years to crowd-source data, this would mark a natural progression from visualisation of individual maps to wider questions about what additional knowledge can be discovered from the data collected. In the new ‘data science’ age, the introduction of real-time data sets introduces a new challenge for web-based mapping applications. The mapping of real-time geospatial systems is technically challenging, but has the potential to show inter-dependencies as they emerge in the time series. Combined geospatial and temporal data mining of realtime sources can provide archives of transport and environmental data from which to accurately model the systems under investigation. By using techniques from machine learning, the models can be built directly from the real-time data stream. These models can then be used for analysis and experimentation, being derived directly from city data. This then leads to an analysis of the behaviours of the interacting systems. (1) The MapTube website: http://www.maptube.org

Urban Informatics

This 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. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This 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. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity