TY - GEN
T1 - Assessing patterns of urban transmutation through 3D geographical modelling and using historical micro-datasets
AU - Santos, Teresa
AU - Rodrigues, Antonio Manuel
AU - Ramalhete, Filipa
N1 - SFRH/BPD/76893/2011
UID/SOC/04647/2013
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
KW - 3D data
KW - Dasymetric mapping
KW - Exploratory Spatial Data Analysis (ESDA)
KW - Historical micro-datasets
KW - Urban transmutation
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U2 - 10.1007/978-3-319-21404-7_3
DO - 10.1007/978-3-319-21404-7_3
M3 - Conference contribution
AN - SCOPUS:84948978522
SN - 9783319214030
VL - 9155
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 32
EP - 44
BT - Computational Science and Its Applications - ICCSA 2015 - 15th International Conference, Proceedings
PB - Springer
CY - Cham
T2 - 15th International Conference on Computational Science and its Applications, ICCSA 2015
Y2 - 22 June 2015 through 25 June 2015
ER -
