Modeling the route and pattern of Khorramabad urban sidewalk through the Capital Competition Algorithm (MST)

Document Type : .

Authors

• Masomeh Azizi ¹
• mehri azanei ²
• hamid saberi ²
• amir gandomkar ³

¹ PhD student in Geography and Urban Planning, Department of Geography , Najafabad Branch, Islamic Azad University, Najafabad ,Iran.

² Assistant professor,Tourism Reserch Center , Najafabad Branch, Islamic Azad University, Najafabad, Iran.

³ Assistate professor, Tourism Reserch Center , Najafabad Branch, Islamic Azad University, Najafabad, Iran.

10.30495/jupm.2021.27289.3782

Abstract

Today, urban activities, commuting, and communications at the city level have changed greatly, and these changes have been without regard to environmental conditions and the favorable human environment, so that it has provided many problems, especially for humans. . In the past, the design of roads, spaces and spatial communications has been such that special attention has been paid to humans as the main users. The pedestrian movement is considered as one of the strategies to improve the quality of the urban environment. This research has been carried out with the aim of presenting a model of urban implementation in Khorramabad city with an approach in terms of applied purpose and in terms of methodology, descriptive research based on model and software studies to achieve the goal of 20 indicators in 4 categories. It has been used through the MST Minimal Span Tree Algorithm in Matlab 2016 software environment and the Network Analyst Tools process in ArcGIS software environment has been used to spatialize the indicators. The results show that 11758591.7 square meters, ie 29.43% of the area of ​​Khorramabad city has a completely suitable condition for the construction of sidewalks. Also, the spatial analysis of Khorramabad city shows that 5 optimal routes for the development of sidewalks. This city includes 1: the distance between 22 Bahman Square, Velayat Boulevard, 60 meters from East Boulevard to Enghelab Alley, 2: Shahid Motahari St., Shariati Boulevard, Asadabadi St. and Mojahedin Islam Sq., 3: Imam Khomeini Sq. Hussein (AS) Shaghayegh Square, 4: Imam and Alavi St., Karim Khan Zand St. and 5: Baharestan Blvd.

Keywords

• Sidewalk
• Algorithm
• Colonial Competition
• Khorramabad
• Gis

20.1001.1.22285229.1401.13.51.12.5

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References

1. Akhavan, Armin; Salehi, Ismail; Toghyani, Shirin (2018), Evaluation of the effect of environmental-physical factors on the vitality and quality of urban streets (Case study: Rare and Revolution streets of Sari, Geography and environmental sustainability, Volume 8, Number 27, pp. 2929-15 2.
2. Afrasiabi, Mena; Arash Sadri and Afsaneh Daghestani (2015), The Impact of Pedestrian Walking on Increasing Social Interactions in Urban Spaces, 2nd International Conference and 4th National Conference on Architecture, Restoration, Urban Planning and Sustainable Environment, Hamedan, Permanent Secretariat of the Conference
3. Bastin, Ali, Ziari, Keramatullah, Pourahmad, Ahmad, Hatami Nejad, Hossein. (2018), Measuring and evaluating the effects of good urban governance on the viability of cities (Case study: Bushehr. Journal of Urban Research and Planning, 9 (34), 1-18. 4
4. Bahr al-Ulumi, Zahra (2016), Reasons for the vitality of public spaces in Italy through history to the present day. Quarterly Journal of Oriental Art and Civilization, Volume 14, Number 4, p. 42-31. 5.
5. Jahanshah Lu, Laia; Amini, inspiration; (2006), Urban Planning and its Role in Achieving Sustainable Urban Transportation, 7th Iranian Conference on Transportation and Traffic Engineering, Tehran.
6. Sadeghi, Zohreh, (2010), Indicators of growth and development of facilities and transport infrastructure and traffic in Isfahan metropolis and its performance in 2003 and 2009, Isfahan Municipality, Deputy of Transportation and Traffic. 7.
7. Alizadeh Moghadam, Samira, Zakerian, Maliheh, Tashkari Bafghi, Babak. (2018) Redesigning the pedestrian path with the approach of improving the quality of people's presence in the historical context of Yazd, a case study: walking on Farokhi Street in Yazd. Journal of Urban Research and Planning, 9 (34), 133-148.
8. Fassihi, Habibollah, Prizadi, Taher, Karami, Tajuddin. (2019). Investigating the role of sidewalks in the vitality of public spaces Case study: Pedestrian sanctuary sidewalks. Sustainable City Quarterly, 2 (4), 1-15. doi: 10.22034 / jsc.2020.189423.1040 9.
9. Gharib, Fereydoun, (2004) Feasibility study of creating pedestrian and bicycle paths in the area of ​​Old Tehran, Journal of Fine Arts, No. 2004, 19 10.
10. Mousavi, Seyedeh Saghar, Shakur, Ali. (2018), The study and role of urban signs with emphasis on the identification of space (Case study: Shahid Chamran Boulevard, Shiraz). Journal of Urban Research and Planning, 9 (35), 1-10. 11.
11. Mirzaei, Khalil, Mohammadzaki, Ahmad. (2016), Evaluation of social effects of sidewalk construction on 15 Khordad Street, located in District 12 of Tehran Municipality (second phase) Quarterly Journal of Urban Research and Planning, 7 (24), 121-142. 12.
12. Nourian, Farshad, Khakpour, Amin, Karbalaei Hosseini Ghiasvand, Abolfazl. (2018) Evaluation of the proposed areas of the detailed plan for urban green space use using network analysis (ANP) in (GIS) (Case study: Javadieh area, 16th district of Tehran Journal of Urban Research and Planning, 9 (35), 97 -110.
13. Amphoux, P. (1998) The concept of atmosphere, Irec-Epel:Lausanne
14. Aplin, K. (2012). Smoke emissions from industrial western Scotland in 1859 inferred from Lord Kelvin’s atmospheric electricity measurements. Atmospheric Environment, 50, 373–376.
15. Blocken, B., & Carmeliet, J. (2004). Pedestrian wind environment around buildings: Literature review and practical examples. Journal of Thermal Envelope and Building Science, 28(2), 107–159.
16. Blocken, B., Hooff, T., & Janssen, W. (2012). CFD simulation for pedestrian wind comfort and wind safety in urban areas: General decision framework and case study for the Eindhoven University campus. Environmental Modeling & Software, 30, 15–34.
17. Borgnat, P., Abry, P., Flandrin, P., Robardet, C., Rouquier, J.-B., & Fleury, E. (2011). Shared bicycles in a city: a signal processing and data analysis perspective. Advances in Complex Systems, 14(3), 415e438.
18. Carmona, M (2003) Public places, Urban spaces, Architectural Press.
19. Chapman, J. (2009) Design for emotional durability, Design, Vol. 25, No. 4, pp. 29-35.
20. Christ, Wolfgang (2000) Public versus private space. Paper presented at the International Symposium, IRS, Erkner bei Berlin, March, pp.173-188.
21. Cowan, Robert (2002) Urban design guidance, London Urban Design Group.
22. Grieves, R. M., & Jeffery, K. J. (2017). The representation of space in the brain Behavioural Processes, 135, 113–131. https://doi.org/10.1016/j.2016.12.012.
23. Li, G. and Wang, Q. 2007. Measuring the Quality of Life in City of Indianapolis by Integration of Remote Sensing and Census Data. International Journal of Remote Sensing. Vol. 28. (2): 249.
24. Lowen, ¨ H., Krukar, J., & Schwering, A. (2019). Spatial learning with orientation maps: The influence of different environmental features on spatial knowledge acquisition. ISPRS International Journal of Geo-Information, 8(3), 149. https://doi.org/10.3390/ ijgi8030149.
25. Madanipour, Ali (2007). Why do we need investing in public space?. Newcastle university.
26. Madanipour, Ali (2010). Whose Public Space? International case studies in urban design and development. First published by Routledge.
27. Madanipour, Ali (2015). Urban Design and Public Space , Newcastle University, Newcastle upon Tyne, UK
28. Manley, E., & Cheng, T. (2018). Exploring the role of spatial cognition in predicting urban traffic flow through agent-based modelling. Transportation Research Part A: Policy and Practice, 109, 14–23. https://doi.org/10.1016/j.tra.2018.01.020.
29. Manley, E., Orr, S., & Cheng, T. (2015). A heuristic model of bounded route choice in urban areas. Transportation Research Part C: Emerging Technologies, 56, 195–209.
30. Marshall, S., Gil, J., Kropf, K., Tomko, M., & Figueiredo, L. (2018). Street network studies: From networks to models and their representations. Networks and Spatial Economics, 18(3), 735–749. https://doi.org/10.1007/s11067-018-9427-9.
31. Nadel, L. (2013). Cognitive maps. In D. Waller, & L. Nadel (Eds.), Handbook of spatial cognition (pp. 155–171). Washington, DC: American Psychological Association.
32. Omer, I., & Kaplan, N. (2017). Using space syntax and agent-based approaches for modeling pedestrian volume at the urban scale. Computers, Environment and Urban Systems, 64, 57–67. https://doi.org/10.1016/J.COMPENVURBSYS.2017.01.007.
33. Omer, I., & Kaplan, N. (2019). Structural properties of the angular and metric street network’s centralities and their implications for movement flows. Environment and Planning B: Urban Analytics and City Science, 46(6), 1182–1200. https://doi.org/ 1177/2399808318760571.
34. Rodríguez, D. A., Merlin, L., Prato, C. G., Conway, T. L., Cohen, D., Elder, J. P., … Veblen-Mortenson, S. (2015). Influence of the built environment on pedestrian route choices of adolescent
35. Tomko, Martin, & Winter, Stephan (2013). Describing the functional spatial structure of urban environments. Computers, Environment and Urban Systems, 41, 177–187. https://doi.org/10.1016/j.compenvurbsys.2013.05.002.
36. Torrens, P. M. (2014). High-fidelity behaviours for model people on model streetscapes. Annals of GIS, 20(3), 139–157. https://doi.org/10.1080/19475683.2014.944933.
37. Transport for London. (2018). Walking action plan. London: Mayor of London. http://conttfl.gov.uk/mts-walking-action-plan.pdf?intcmp=54543. (Accessed 1 February 2020).).