2013
DOI: 10.4018/jagr.2013010101
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Intra-Urban Analysis of Commercial Locations A GIS-Based Approach

Abstract: The urban landscape is an interspersed mixing of residences, shops, theatres, parks, natural areas, and a multitude of other uses. From the early days of the central markets, to the planned downtown, to the heavily planned super-regional shopping complexes, the commercial areas within this urban landscape have evolved. There has been considerable research conducted on analyzing the commercial structure of urban environments in an attempt to better understand the nature of retailing and its resultant impacts on… Show more

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Cited by 5 publications
(2 citation statements)
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“…In addition to centrality, clustering is another key attribute of commercial space distribution [11], leading us to incorporate spatial clustering analysis following Space Syntax analysis of the urban street network. Studies have shown that spatial clustering algorithms can scientifically classify groups of clusters based on the geographical proximity among a large number of unsorted urban elements [28,29].…”
Section: Introductionmentioning
confidence: 99%
“…In addition to centrality, clustering is another key attribute of commercial space distribution [11], leading us to incorporate spatial clustering analysis following Space Syntax analysis of the urban street network. Studies have shown that spatial clustering algorithms can scientifically classify groups of clusters based on the geographical proximity among a large number of unsorted urban elements [28,29].…”
Section: Introductionmentioning
confidence: 99%
“…Hence, the integration of the two models enables the decision maker to analyse the alternatives based on not only its similarity to the ideal solution but also the decision maker's optimism degree (Milad Moradi, Delavar, & Moshiri, 2015). Extensive research have been undertaken to propose a reliable framework based on MCDM algorithms for land use planning (Matthews, Sibbald, & Craw, 1999;Mosadeghi et al, 2015;Storie, 2013;Su-xia & He-bing, 2010;Zhang, Li, & Fung, 2012). Zhang et al (2012) used GIS-based multi criteria decision making for conflict resolution in land use planning.…”
Section: Introductionmentioning
confidence: 99%