By Fernando Bacao, Maribel Yasmina Santos, Marco Painho
This is a ebook is a suite of articles that may be submitted as complete papers to the AGILE annual overseas convention. those papers wade through a rigorous evaluate strategy and document unique and unpublished basic clinical learn. these released hide major learn within the area of geographic info technological know-how platforms. This 12 months the point of interest is on geographic info technological know-how as an enabler of smarter towns and groups, hence we think contributions that aid visualize the function and contribution of GI technology of their development.
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Additional info for AGILE 2015: Geographic Information Science as an Enabler of Smarter Cities and Communities
International Journal of Geographical Information Science, 27(12), 2509–2532. , & Frank, A. U. (2013). Cognitive transactions: A communication model. In: T. Tenbrink, J. G. Stell, A. Galton, & Z. ), COSIT (Vol. 8116, pp. 129–148). Lecture Notes in Computer Science. Berlin: Springer. , & Krüger, A. (2009). Guest editorial: Does place have a place in geographic information science? Spatial Cognition & Computation: An Interdisciplinary Journal: Special Issue: Computational Models of Place, 9(3), 171−173.
A Semantic Region Growing Algorithm: Extraction of Urban Settings 23 The thematic or semantic aspect of spatial features is managed through a tagging system where each geometric feature is described by an arbitrary number of tags. As the OpenStreetMap project evolved and prospered over time, its community developed a set of tagging guidelines that describe which tags should be used for a speciﬁc feature. Before contributing new information to the database, mappers are asked to carefully read these guidelines.
Therefore, we collected data from Metro Extracts,2 a website that provides parts of the OSM datasets for cities and their surroundings. com/. A Semantic Region Growing Algorithm: Extraction of Urban Settings 27 Fig. 2 Visualization of the results identiﬁed by the semantic region growing algorithm in Vienna downloaded and parsed the datasets for Vienna and London. 0005 degrees, and preprocessed the OSM data by assigning the nodes and their tags to the cells. The rules for our description are based on the following assumptions.
AGILE 2015: Geographic Information Science as an Enabler of Smarter Cities and Communities by Fernando Bacao, Maribel Yasmina Santos, Marco Painho