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Using Trieste (Italy) as a case study, it compares traditional segregation indicators such as Location Quotients and the Index of Segregation with spatial alternatives built on Kernel Density Estimation, including the S index and an early Index of Diversity version.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/template/","Template",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/template/paper-templates/","Paper 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do traditional segregation measures often fall short in migration studies?","Question",{"text":62,"@type":63},"Many established indices are aspatial, so they do not account for relationships among people across a city and can miss local spatial non-uniformity and visualization of segregation.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"What spatial methods does the paper emphasize for analyzing immigrant residential distribution?",{"text":67,"@type":63},"The paper focuses on density-based approaches using Kernel Density Estimation functions, including an S index and a first version of an Index of Diversity.",{"name":69,"@type":60,"acceptedAnswer":70},"How does the study use Trieste (Italy) in its comparison of methods?",{"text":71,"@type":63},"Trieste serves as a case study to test and compare traditional indices (such as Location Quotients and the Index of Segregation) against spatial indices derived from density estimation.","https://schema.org",{"og:url":32,"og:type":74,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":76,"canonical":32},"index,follow",{"doc_id":78,"site_id":7},168670,1790496686,{"code":4,"msg":81,"data":82},"success",[83,88,93,98,103,108,113,118,122],{"id":84,"doc_module":22,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},11,"Presentations",90,"presentations",{"id":89,"doc_module":22,"doc_module_name":25,"category_name":90,"show_sort_weight":91,"slug":92},12,"Resumes",80,"resumes",{"id":94,"doc_module":22,"doc_module_name":25,"category_name":95,"show_sort_weight":96,"slug":97},14,"Invoices",70,"invoices",{"id":99,"doc_module":22,"doc_module_name":25,"category_name":100,"show_sort_weight":101,"slug":102},15,"Posters",60,"posters",{"id":104,"doc_module":22,"doc_module_name":25,"category_name":105,"show_sort_weight":106,"slug":107},16,"Social 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Analysis of Foreign Immigration and Spatial Patterns in Urban Areas. \u000bDensity Estimation and Spatial Segregation\nGiuseppe Borruso\nUniversity of Trieste, Department of Geographical and Historical Sciences\u000bP. le Europa 1, 34127 Trieste, Italy\n\u0013 HYPERLINK \"mailto:giuseppe.borruso@econ.units.it\" \u0014giuseppe.borruso@econ.units.it\u0015\nAbstract. The paper is focused on the analysis of immigrant population with particular reference to their spatial distribution and the tendency to cluster in some parts of a city, with the risk of generating ethnic enclaves or ghettoes. 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-based method. 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 traditional indices, as Location Quotients and the Index of Segregation, to different, spatial ones, both based on Kernel Density Estimation functions, as the S index and the first version of an Index of Diversity. \u000bKeywords:GIS; Geographical Analysis; Foreign Immigration; Spatial Segregation; Density Estimation; Trieste (Italy)\n1   On qualitative and quantitative methods for the analysis of immigrants at urban level\nThe analysis on migrations, as correctly observed by Krasna [1] can rely on a mixed combination of methods and tools, both quantitative and qualitative ones. The former ones benefit from the diffusion of spatial analytical instruments and information systems, as well as from the huge availability of digital data and computation power unthinkable since few years ago. That allows filtering data and preparing information for the evaluation to be performed by the scholar on the phenomenon under examination. We can remind Tobler’s first law of geography [2], stating that every phenomenon over space is linked to all the other ones, but closer phenomena are more related to each other than farther ones, and therefore understand that the geographical space is capable of being analyzed by means of such quantitative methods, but also that no universal rules can be established, given the different characteristics and peculiarities of places over the Earth’s surface. The scholars involved in migration research should therefore rely also on qualitative methods in order to integrate their studies, with the difficult task of interpreting correctly what is happening over space.\nWith reference to migration studies, and particularly when these are referred to the urban environment, several analyses have been carried out in recent years to examine their spatial distribution, the characteristics of settlements and, more recently, the phenomena of residential segregation and the impact of migrants over the job market and the economy as a whole,in parallel with the migrants’ rooting in space as a structural component of society and economy. Researchers have focused their attention on different indicators in order to examine the characters of the spatial distribution of migrant groups, particularly in order to highlight the trends towards concentration rather than dispersion or homogeneity, or, still, the preferences for central rather than peripheral areas. The attention however is in particular focused on the analysis of phenomena related to residential segregation, at risk particularly in areas where a too high concentration of a single immigrant group is present if compared to the local residents such that ghettoes or ‘ethnic islands’ take place.\nSome authors, as recalled by Cristaldi [3], draw their attention on some aspects related to segregation, as particularly the level of residential concentration, the assimilation and encapsulation. The indices generally used","cbCaiuFhmTO0IsFv","https://ap.wps.com/l/cbCaiuFhmTO0IsFv","docx",978317,"English","# Abstract\n# Introduction\n## Background on migration research methods\n## Urban spatial distribution and residential segregation\n# Segregation indicators and limitations\n## Dissimilarity-based segregation indices\n## Scale effects and zoning dependence\n## Data constraints and spatial relations","[{\"question\":\"Why do traditional segregation measures often fall short in migration studies?\",\"answer\":\"Many established indices are aspatial, so they do not account for relationships among people across a city and can miss local spatial non-uniformity and visualization of segregation.\"},{\"question\":\"What spatial methods does the paper emphasize for analyzing immigrant residential distribution?\",\"answer\":\"The paper focuses on density-based approaches using Kernel Density Estimation functions, including an S index and a first version of an Index of Diversity.\"},{\"question\":\"How does the study use Trieste (Italy) in its comparison of methods?\",\"answer\":\"Trieste serves as a case study to test and compare traditional indices (such as Location Quotients and the Index of Segregation) against spatial indices derived from density estimation.\"}]","On qualitative and quantitative methods for the analysis of immigrants at urban level - Qualitative and quantitative spatial analysis methods | DOCX",1788235613,6]