Explaining the relationship between the use of pedestrians from urban spaces with integration and commercial-service uses, case study: the Chustduzan poor neighborhood in Tabriz

Document Type : Research Paper

Authors

• H Babapoor Fatehi ¹
• K Habibi
• Sh Toghyani ²
• F Ahmadi ³

¹ Department of Urban planning , Faculty of Art, Architecture & Urban Planning , Najafabad Branch, Islamic Azad University,Najafabad, Iran

² Department of Urban planning , Faculty of Art, Architecture & Urban Planning , Najafabad Branch, Islamic Azad University,Najafabad, Iran

³ گروه شهرسازی، دانشکده هنر، معماری و شهرسازی، واحد نجفآباد، دانشگاه آزاد اسلامی، نجفآباد، ایران.

Abstract

Predicting intensity and various uses of urban open spaces is an important urban open space management issue. Also, it is an important challenge for urban planners and designers to pursue their goals in urban environment. In a research that examines the use of urban spaces in zone 4 of Tabriz city, a predictive model has been developed using Space Syntax method and Regression. An encounter model has been used to survey the pedestrian movement in the city. Some shortcoming, that is not able to specify the effect of all dependent and independent several research experiments indicated that space syntax technique can develop models that can interpret and predict pedestrian movement in regard to urban morphology, regardless of this capability it has variables and their combination as a factor on pedestrian movements.This study examines the effect of parameters of the integration and the number of commercial uses in the forecast number of pedestrians were studied, it was shown that the influence of both parameters in predicting the number of pedestrians better results than the influence of each parameter alone in predicting that the number of pedestrian, As the correlation between the two parameters, integration and commercial uses at the same time the number of pedestrians; 0.736, and the correlation between them, separately, the number of pedestrian sequential are 0.453 and 0.587. Finally the finding summaries of this study offers a model that can predict the number of pedestrian in urban space accurately.

Keywords

• space syntax
• Regression
• pedestrian
• Urban space
• Tabriz

20.1001.1.22285229.1396.8.31.3.1

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