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Two Phase Temporal-Spatial Autocorrelation of Urban Patterns: Revealing Focal Areas of Re-Urbanization in Tel Aviv-Yafo

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Abstract

A new two-phase temporal-spatial analysis technique is presented for exploring core areas of re-urbanization in complex patterns of urban change. The Local Autocorrelation of Pearson (LAoP) technique first computes temporal Pearson correlations between time series of data for each sub-area and the city’s average time series and then computes the local Moran autocorrelation (LISA) of these temporal correlations. This technique was implemented on Construction Initiation (CI) data for the city Tel Aviv-Yafo since the mid 1970s, where complex patterns evolved through spontaneous socio-economic processes, individual and corporate behavior and local and national planning policies. Comparing the results from the temporal-spatial autocorrelation analysis on CI data, with those of the accumulated built-up areas enhances the understanding of the patterns of re-urbanization in Tel Aviv-Yafo and the detection of new core areas of development.

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Authors and Affiliations

  1. Faculty of Architecture and Town Planning, Technion, IIT, Technion city, 36000, Haifa, Israel

    Idan Porat & Amnon Frenkel

  2. Faculty of Civil and Environmental Engineering, Technion, 36000, Haifa, Israel

    Maxim Shoshany

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  1. Idan Porat
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  2. Maxim Shoshany
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  3. Amnon Frenkel
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Correspondence to Idan Porat.

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Porat, I., Shoshany, M. & Frenkel, A. Two Phase Temporal-Spatial Autocorrelation of Urban Patterns: Revealing Focal Areas of Re-Urbanization in Tel Aviv-Yafo. Appl. Spatial Analysis 5, 137–155 (2012). https://doi.org/10.1007/s12061-011-9065-9

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