Contributions towards smart cities : exploring block level census data for the characterization of change in Lisbon
Contribuinte(s) |
Bação, Fernando José Ferreira Lucas Henriques, Roberto André Pereira |
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Data(s) |
23/05/2016
23/05/2016
07/03/2016
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Resumo |
The interest in using information to improve the quality of living in large urban areas and its governance efficiency has been around for decades. Nevertheless, the improvements in Information and Communications Technology has sparked a new dynamic in academic research, usually under the umbrella term of Smart Cities. This concept of Smart City can probably be translated, in a simplified version, into cities that are lived, managed and developed in an information-saturated environment. While it makes perfect sense and we can easily foresee the benefits of such a concept, presently there are still several significant challenges that need to be tackled before we can materialize this vision. In this work we aim at providing a small contribution in this direction, which maximizes the relevancy of the available information resources. One of the most detailed and geographically relevant information resource available, for the study of cities, is the census, more specifically the data available at block level (Subsecção Estatística). In this work, we use Self-Organizing Maps (SOM) and the variant Geo-SOM to explore the block level data from the Portuguese census of Lisbon city, for the years of 2001 and 2011. We focus on gauging change, proposing ways that allow the comparison of the two time periods, which have two different underlying geographical bases. We proceed with the analysis of the data using different SOM variants, aiming at producing a two-fold portrait: one, of the evolution of Lisbon during the first decade of the XXI century, another, of how the census dataset and SOM’s can be used to produce an informational framework for the study of cities. |
Identificador |
http://hdl.handle.net/10362/17446 201111942 |
Idioma(s) |
eng |
Direitos |
openAccess |
Palavras-Chave | #Data mining #Self-Organizing Map #Smart City #Geo-SOM #Clustering #Geographic Information Science #Census |
Tipo |
masterThesis |