The measurement, identification and interpretation of spatial-temporal patterns are often dependent on the geometrical schemes used to divide land into discrete units/objects. Because anisotropy is a common characteristic of spatial surfaces, heterogeneity within artificial boundaries should be assumed. Hence, non-stationarity of datasets often causes aggregation problems and mis-interpretaions, commonly known as ecological fallacy. In multi-temporal analysis, when for different time-periods, data is collected for distinct sets of spatial objects – different schema -, modifiable areal unit problems become also an important issue. This article demonstrates how datasets' coherence in terms of spatial boundaries and time periods can be created using auxiliary geographical information. The motivation for the present article is the attempt to create a small-area database from Portuguese census data, which will for the first time allow the dynamic analysis of demographic patterns for a specific study-area, the Lisbon local council. Census tracts' data are available for three periods: 1991, 2001 and 2011. Historical data analysis is possible between the two first periods but not for the 2011 dataset; this is so because complex geometries did not allow for a coherent coding of observations. Through the use of Geographical Information Systems (GIS), census data was allocated to common areas taking into account a weighting scheme dependent on asymmetric mapping based on auxiliary data (area of building blocks). It is believed that the results obtained minimize the error associated with spatial aggregation. Finally, the article exemplifies the potential benefits of the methodology used for future research on the evolution of demographic patterns in Portugal.
|Title of host publication||Proceedings 2012 - The 15th AGILE International Conference on Geographic Information Science|
|Editors||Jerome Gensel, Didier Josselin, Danny Vandenbroucke|
|Place of Publication||Avignon|
|Publication status||Published - 1 Jan 2012|
|Name||Bridging the Geographic Information Science|