Abstract
The increasing volume of empty houses in historical cities constitute a challenge in times of economic crisis and acute housing needs. In order build coherent guidelines and implement effective policies, it is necessary to understand long-term patterns in city growth. The present work analyses urban dynamics at the micro level and present clues concerning transmutation in Lisbon, Portugal, using 3D geographical modelling to estimate potential housing supply. The recent availability of detailed demographic historical micro-datasets presents an opportunity to understand long-term trends.
Integrating cartographic and altimetric data, vacant houses of the city are mapped and attributes like area, volume and number of floors are estimated. Then, the potential for social housing is evaluated, based on state owned buildings morphology. Exploratory Spatial Data Analysis (ESDA) help to highlight trends at a finer scale, using advanced geovisualization techniques. The challenge of working with distinct data sources was tackled using Free and Open Source (FOSS) Geographical Database Management Systems (GDBMS) PostgreSQL (and spatial extension PostGIS); this facilitated interoperability between datasets.
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Santos, T., Rodrigues, A.M., Ramalhete, F. (2015). Assessing Patterns of Urban Transmutation Through 3D Geographical Modelling and Using Historical Micro-Datasets. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2015. ICCSA 2015. Lecture Notes in Computer Science(), vol 9155. Springer, Cham. https://doi.org/10.1007/978-3-319-21404-7_3
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