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  • The study of inequality of socioeconomic phenomena in urban areas may provide useful recommendations for targeted social policy, local measurements, urban planning and investment strategies. Among various tools we select spatial heterogeneity indexes, spatial autocorrelation measures, the LISA analysis and the spatial hierarchical clustering. The most promising outputs we obtain from last two methods. LISA allows indicating seeds of segregation and detecting localities even not nominated by experts yet. The LISA analysis reveals clusters of anomalous values, but results are heavily influenced by neighbourhoods. The methods of spatial hierarchical clustering are implemented in a new database application which is under development. This application standardizes data, calculates measures of similarity among objects, applies various methods of aggregation and applies different spatial relationships. First results show the ability to identify homogeneous clusters inside selected localities; nevertheless a continuous extended research is required to optimise these methods.
  • The study of inequality of socioeconomic phenomena in urban areas may provide useful recommendations for targeted social policy, local measurements, urban planning and investment strategies. Among various tools we select spatial heterogeneity indexes, spatial autocorrelation measures, the LISA analysis and the spatial hierarchical clustering. The most promising outputs we obtain from last two methods. LISA allows indicating seeds of segregation and detecting localities even not nominated by experts yet. The LISA analysis reveals clusters of anomalous values, but results are heavily influenced by neighbourhoods. The methods of spatial hierarchical clustering are implemented in a new database application which is under development. This application standardizes data, calculates measures of similarity among objects, applies various methods of aggregation and applies different spatial relationships. First results show the ability to identify homogeneous clusters inside selected localities; nevertheless a continuous extended research is required to optimise these methods. (en)
Title
  • Methods of Spatial Clustering in a City
  • Methods of Spatial Clustering in a City (en)
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  • Methods of Spatial Clustering in a City
  • Methods of Spatial Clustering in a City (en)
skos:notation
  • RIV/61989100:27350/12:86080311!RIV13-GA0-27350___
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  • P(GA403/09/1720)
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  • 149788
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  • RIV/61989100:27350/12:86080311
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  • spatial autocorrelation; LISA; spatial hierarchical clustering; spatial heterogeneity (en)
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  • [8C51B1D57EF0]
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  • Brno
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  • Brno
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  • Geography and Geoinformatics: Challenge for Practise and Education : proceedings of 19th international conference : [Brno, September 8-9, 2011]
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  • Horák, Jiří
  • Soukup, Pavel
  • Ivan, Igor
  • Inspektor, Tomáš
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http://linked.open.../riv/zahajeniAkce
number of pages
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  • Masaryk University
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  • 978-80-210-5799-9
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  • 27350
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