The relation between urban vitality and sense of place attachment (Case study: Qaen city)

Subject Areas :

ahmad asadi ¹ , mehdi mododi ² , Saeed Hossein Abadi ³

1 - Assistant Professor of Geography & Urban Planning, Bozorgmehr University of qaenat, qaen, Iran.
2 - Assistant Professor of Geography & Urban Planning, Bozorgmehr University of qaenat, qaen, Iran.y
3 - Assistant Professor of Geography & Urban Planning, Bozorgmehr University of qaenat, qaen, Iran.

Received: 2018-10-22 Accepted : 2019-10-18 Published : 2020-04-20

Keywords: urban vitality, sense of place attachment, K-nearest neighbor, random forest algorithm, Qaen city,

Abstract :

       The vitality is one of the main criteria for cities with high quality planning and design. Lively urban environments create social interactions, increase social capital and place attachment. The aim of this paper is to analyze the relationship between urban vitality and Place attachment in Qaen city. This study is a survey research and data collection tool is a questionnaire. The sample size is 382 citizens of Qaen city, which is calculated using the Cochran formula. Independent variables of this research are urban vitality indicators (access, social dynamics, economic vitality, urban security, street design, furniture, urban spaces lighting, urban landscape, and readability) and dependent variable, is sense of place attachment. For analysis of the relationship between variables, the k-Nearest Neighbors model (K-NN) and Randomized Forest Algorithm (RF)have been used. The vitality indicator consists of 28 items, that averages of 17 items are not at the appropriate level and 11 of them are at acceptable level. In general, the urban vitality is low in Qaen city. Also, the mean of the sense of place is at a moderate level. According to the output of the models, the K nearest neighbor method provides better results than the random forest model. K-NN model simulated impact of   vitality on   place attachment with a correlation coefficient of 0.82 and an error level of 0.66 and a risk of estimating of 0.435. Therefore, this model can correctly simulate place attachment in 57% of cases. Based on the model generated by the random forest algorithm, the access variable has the most and legibility has the least effect on the sense of place attachment in the city of Qaen.
Extended Abstract
Introduction:
         Vitality as a component of the overall quality of urban design of an environment can affect the location Belong and Improve the social health of citizens Hence the need to enhance the vitality of urban spaces and urban neighborhoods emerge as one of the paradigms in urban planning. The ultimate goal of urban planning is to provide suitable living conditions in the city and urban residential environments that are closely related to the concept of vitality and livability of the city. A city where people live should be inviting and create a passionate environment. In the cities of Iran, the component of vitality has not received much attention. Influenced by the dominance meaningless without regard to the background and nature of traditional neighborhoods, the conquest of material factors over the spiritual, and the dominance of machines over humans. And used at the same level as urban divisions. The continuation of such a trend has made the civic life of neighborhoods and urban spaces lack vitality. At the same time, the physical spaces of neighborhoods in Iranian historical cities were influenced by various factors, including cultural, social, natural, and so on. Increasing urban vitality, on the one hand, makes the population living in a city more willing to stay, and on the other, it also attracts a population that intends to migrate to the metropolitan areas of the country. In this research, we try to study the relationship between the vitality of urban spaces and the sense of belonging of citizens to the city of Qaen. The importance of this research is that location belongs to an important role in the development of any city; On the other hand, location affiliation reduces migration from one region to another. This is largely felt in the South Khorasan region. The increase in location Belong is influenced by various factors, one of which is urban vitality. Therefore, the purpose of this study is to model the relationship between urban vitality and sense of belonging using k-nearest distance and random forest algorithm in Qaen.
Methodology:
        The research method is applied in terms of descriptive-analytic nature and the method of data collection is library and field method. The population of the study is the population of Qaen with about 42323 populations (according to the year 1395). The sample size is based on Cochran method of 382 persons and the sampling method is simple random. This study investigates the relationship between vitality index and sense of belonging. The vitality index includes variables such as accessibility, social dynamics, economic vitality, urban security, passage design, furniture, urban lighting, urban landscape and readability. In this study variables of vitality index are considered as independent variables and sense of belonging as dependent variable. In this study, K-nearest neighbor and random forest were used to model the independent variables of urban vitality and the dependent variable of sense of belonging.
Results and discussion:
         Among the variables related to the urban vitality index, urban access had the highest score and urban furniture had the lowest score. The sense of belonging in the city of Qaen is at a moderate level, with only "this is where I want it" somewhat lower. Thus, the level of satisfaction of the citizens of Cain is at a moderate level, and none of the sense of belonging is at a very high level. In this study, two methods of K nearest neighbor and random forest were used to model the independent variable (urban vitality) and the dependent variable (sense of belonging). Performance evaluation of the K-NN model shows that the model simulated the sense of belonging with a correlation coefficient of 0.82 with a 0.66 error rate and a risk estimate of 0.435. Therefore, this model was able to correctly simulate the sense of belonging in 66% of cases. Evaluation of other statistical indices shows that this model overall simulates the sense of belonging less than the observed value. That is, the model shows a negative bias. But this bias is not much to distort the model's results. As such, the mean and standard deviation of the sense-of-belonging variable simulated by the model have very little difference with the observed values of these two statistical indicators. Evaluation of model validation criteria shows that with 200 trees in addition, the best results are obtained with the least modeling error but also the error rate is stable and achieves a consistent trend. As this model was able to accurately simulate the sense of belonging based on independent variables with error of 0.82, 0.68 in 32% of cases. Important in this modeling process is the negligible bias. t is noteworthy that with respect to residual mass factor (CRM), although the model overall has a negligible bias, the simulation values are more than the observed values. But fitting the observed and simulated sense of belonging values and comparing the mean and standard deviation of these two data sets show that the random forest model failed to estimate the upper and lower values of the sense of belonging variable with a slight error, as in the K-NN model. In general, the K-NN model exhibits much higher flexibility than the RF model in simulating the sense of belonging. According to the outputs of the models, the K-nearest neighbor method had better results than the random forest model. The performance of the K-NN model show that the model simulated the sense of belonging with a correlation coefficient of 0.82 with an error rate of 0.66 and an estimated risk of 0.3535. Therefore, this model was able to correctly simulate the sense of belonging in 66% of cases.
Conclusion:
          According to the model created by random forest algorithm respectively accessibility variables, social dynamics, economic vitality, urban security, passage design, furniture, urban spaces lighting, urban landscape and readability have the most to least effect on sense of belonging in Qaen city. The reason that accessibility variables have the most impact on sense of belonging is due to the existence of proper passageways in the city of Qaen, and some variables such as simplicity and urban landscape and readability that have the least impact on sense of belonging are due to their weakness in the city. The vitality index consists of 28 items with an average of 17 not good and 11 items are acceptable. Also, the sense of belonging is at a moderate level. One of the reasons for the weakness of urban vitality in Qaen is the weak economy of the city. This is also due to the lack of appropriate potentials for private sector investment.

References:

1. Abbaszadeh, G., and Hosseinpour, A. (2012): Residential Cities; Benefits of Urban Environmental Planning, First Edition, Mashhad, Tahan.


2. Shaykh Baygloo,R. (2017), Citizens’ Perception on Urban Responsive Environments and itsRole in Place Attachment (Case Study: City of Arak), Geography and Urban Space Development, Fourth Year, No. 1 (6th consecutive), pp. 77-98.


3. Sheykhi, M., Amini, S., Nezami, A. (2015). A Comparative Study of the Feeling of Place Attachment in Formal Settlements & Informal Settlements (Parand New Town and Nasimshahr). Social Sciences, 22(69), 45-74.

2. Adibi, F. and Azimi, A. (2011): Explaining Security in Urban Environment Based on Physical and Design Parameters (case study: Babolsar City), Geographical Survey of Environmental Planning, No. 15, pp106-81.


3. Bahrampour, A., Modiri, A. (2015). Study of Relationship Between Residents Satisfaction from Living Environment and their Attachment Sense in Kowsar High-Rise Residential Complex. Honar-Ha-Ye-Ziba: Memary and Shahrsazi, 20(3), 85-94.


4. Breiman, L. (2001): Random forests. Machine learning. 45(1): 5-32.


5. Charkhchian, M. (2009): An Analytical Study of Factors Affecting Increased Attachment to Public Spaces of the City with Emphasis on Activity Diversity, PhD dissertation, Iran University of Science and Technology.


6. Emami, A., Bazdar, M., Safari, M., Farahnaki, R. (2013). The Determination of Relationship between Sense of Belonging and its Social Indicators, Case Study: Ziarat Village- Golestan. Armanshahr Architecture & Urban Development, 10(21), 11-21.


7. Florek, M. (2011): "No place like home: Perspectives on place attachment and impacts on city management". Journal of Town & City Management. 1 (4): 346–354.


8. Ghorbani, R., Jame Kasra, M. (2010): Pedestranization as a new approach for the renewal of urban centers A case study of Tarbiat pedestrian way of Tabriz. Journal of Urban - Regional Studies and Research, 2(6), 55-72.


9. Habibi, D. (2013): Investigating the Factors Affecting the Vitality and Biodegradability in Historical and Worn Textures (Case Study: Shiraz Sang siah Neighborhood), Iranian-Islamic Studies Quarterly, No. 14, pp. 80-75.


10. Hadipour, G. (2013): Management and Sustainable Urban Development, Conference on Architecture and Urban Development and Sustainable Development, Khavaran Institute of Higher Education.


11. Hastie, T., Tibshirani, R and J. Friedman, (2003): The elements of statistical learning: data mining, inference and prediction. In Sprin- ger series in statistics New York.


12. Izadi, S., Nikokhvi, M., and Samavati, S. (2012): Investigating the Role of Qualitative Components of Pedestrian Territory in the Lifestyle and Efficiency of Urban Streets (Case Study: Hamedan Bou Ali Sina Street), Journal of Tourism Space, First Year, No. 3, pp. 103-118.


13. Karimi, F., Abdollahi, A. (2017). Creating pedestrians to enhance alacrity and vitality in urban spaces (Case Study: Mellat Street, Shahr-e-Kord, between the 21th Muharram Square and Bazaar). Spatial Planning, 7(1), 81-100.


14. Khasto, M., S.R. Navid. (2012). The Effective Factors on Urban Spaces Vitality (Creating a Lively Urban Space with Emphasizing the Concept “Pedestrian Mall”). Hoviatshahr, 4(6), 63-74.


15. Latifi G, Jome Poor M, Gerivani S. (2014): A comparative study of urban livability in neighborhoods case study: southern Majidieh and SaadatAbad, Tehran, Iran. 3. 13 (34) :27-40


16. Mahmoodinejad, F., and Omid Ghane, R. (2013): Investigating the Role of Public Participation in Promoting Diversity and Security in Living in Urban Areas (Case Study: Kalpa Hamadan), Haft Hesar Environmental Studies, Volume 1, Number 3, pp, 66-57.


17. Manzo Lynne and Douglas D. Perkins (2006): Finding Common Ground: The Importance of PlaceAttachment to Community Participation and Planning, Journal of Planning Literature, Vol. 20, No. 4 (May 2006).


18. Mehrabani, E., Mansouri, S., Javadi, S. (2017). Landscape Approach in Creating Vitality in Valiasr Avenue an Emphasis on Creating the Sense of Place*. The Monthly Scientific Journal of Bagh- E Nazar, 14(55), 5-16.


19. Rahimi, L., Jafari, F. (2018). The Measurement of Livability of Historical and Modern Commercial Spaces in the city of Tabriz (Case Study: Tabriz Historic Bazaar and Crystal Tower). Spatial Planning, 7(4), 41-56.


20. Rollero, Chiara; De Piccoli, Norma (2010): "Place attachment, identification and environment perception: An empirical study". Journal of Environmental Psychology. 30 (2): 198–205.


21. Samvati, Sahar., Nikookhooy, Mona. & Izadi, Mohammad (2013) The Role of Vitality and Viability of Urban Streets in Enhancement the Quality of Pedestrian –Oriented Urban Venues, (Case Study: Buali Sina Street, Hamedan, Iran). Journal of Basic and Applied Scientific Research. 3(7)554-561, 2013.


22. Saraei, M., oshnooi, A., rusta, M. (2016). Evaluation of spatial indices belong to old texture residents of the city of Kashan. Geography and Environmental Planning, 27(2), 17-34.


23. Shahyvandi, A., Ghalehnouie, M. Alipour Esfahani, M. (2015): Investigation of Physical Properties and its Impact on the Vitality and Livability of Old Urban Neighborhoods (Case Study of Isfahan Sanbolestan Neighborhood) Iranian Journal of Restoration and Architecture, Fifth Year, No. 9, pp. 26-13.


24. Shataee, Sh., Kalbi, S., Fallah. A., and Pelz, D. 2012. Forest attributes imputation using machine-learning methods and ASTER data: comparison of k-NN, SVR and random forest regression algorithms. International Journal of Remote Sensing, 33(19): 6254-6280.

27. Shiehe, smaiel (2013): Foundations of Urban Planning, Thirty-Fourth Edition, Tehran, University of Science and Technology.


28. Siami, G., Akhtari Takaleh, A., Khanizadeh, M. (2016). Evaluation of economic vivaciousness criteria in historic bazaars of Iran: developing a recreation point of view: the case of Qazvin historic bazaar., 9(34), 1-26.


29. Wilson, D. R. and Martinez, T. R. (2000): Reduction techniques for exemplar-based learning algorithms, Machine Learning, 38(3), pp. 257-286.


30. Zaidin, Nurbazliah, Mohd Ramzi Mohd Hussain, Izawati Tukiman, and Fitrynadia Mohd Shahli (2016): Place Attachment in Relation to Urban Street Vitality, International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 7 No.1.


31. Zanganeh, Y., and Hosseinabadi, S. (2013): An Analysis of Spatial Affiliation and its Affecting Factors in Informal Settlements (Case Study: Eastern Cal Zone Eideghe Sabzevar, Journal of Urban Sociological Studies, Volume 3, Number 8, Pages 162- 131.