Abstract
The paper is focused on the analysis of immigrant population and particularly on some of the characteristics of their spatial distribution in an urban environment. The attention is drawn on examining whenever there is a tendency to cluster in some parts of a city, with the risk of generating ethnic enclaves or ghettoes, therefore analysing also diversity other than the pure spatial distribution. Methods used in the past to measure segregation and other characteristics of immigrants have long been aspatial, therefore not considering relationships between people within a city. In this paper the attention is dedicated to methods to analyse the immigrant residential distribution spatially, with particular reference to density and diversity-based methods. The analysis is focused on the Municipality of Trieste (Italy) as a case study to test different methods for the analysis of immigration, and particularly to compare different indices, particularly traditional ones, as Location Quotients and the Index of Segregation, to different, spatial ones, based on Kernel Density Estimation functions, as the S index, and indices of diversity, as Shannon (SHDI) and Simpson (SIDI) ones as well as another diversity index proposed (IDiv). The different analysis and indices are performed and implemented in a GIS environment.
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Borruso, G. (2009). Geographical Analysis of Foreign Immigration and Spatial Patterns in Urban Areas: Density Estimation, Spatial Segregation and Diversity Analysis. In: Gavrilova, M.L., Tan, C.J.K. (eds) Transactions on Computational Science VI. Lecture Notes in Computer Science, vol 5730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10649-1_18
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