ارزيابي زيست‌پذيري مبتني بر متغيرهاي حس تعلق به مكان (مطالعۀ موردي منطقۀ 1 كلان‌شهر تهران)

Estimating the livability based on the sense of place variables: A case study of Tehran metropolitan, district 1

در ﭼﻨﺪ دﻫﮥ ﮔﺬﺷﺘﻪ، رﺷﺪ ﻓﻨﺎوري و اﺟﺮاي ﻣﺒﺎﻧﯽ ﻣﺪرﻧﯿﺘﻪ در ﺳﺎﺧﺖ ﺷﻬﺮﻫﺎ ﻣﻮﺟﺐ روﻧﺪ ﮐﺎﻫﺸـ ﯽ در زﯾﺴـﺖ ﭘـﺬ ﯾﺮي ﺷﻬﺮﻫﺎ ﺷﺪه اﺳﺖ ﮐﻪ ﺑﻪ اﺛﺮاﺗﯽ ﻧﺎﻣﻄﻠﻮب در ﻓﻀﺎﻫﺎي ﺷﻬﺮي ﻣﻨﺠﺮ ﺷﺪه اﺳﺖ. ﯾﮑﯽ از ﺑﺮﺟﺴﺘﻪ ﺗﺮﯾﻦ اﯾﻦ اﺛﺮات ﮐـﻪ ﻣﯽ ﺗﻮان از آن ﺑﻪ ﻋﻨﻮان آﺳﯿﺐ ﺷﻬﺮي ﻧﺎم ﺑﺮد، اﻓﻮل ارزش ﻫﺎي ﻣﺮﺗﺒﻂ ﺑﺎ ﺣﺲ ﺗﻌﻠﻖ ﺑﻪ ﻣﮑـﺎن در ﺷـﮑﻞ ﮔﯿـ ﺮي اﯾـ ﻦ ﻓﻀﺎﻫﺎ اﺳﺖ. اﯾﻦ اﻣﺮ در ﮐﻼن ﺷﻬﺮﻫﺎ ﺟﻠﻮة ﺑﯿﺸﺘﺮي دارد ﮐﻪ ﻃﺒﯿﻌﺘﺎً رﺷﺪ ﻓﻨﺎوري در آن ﻫـﺎ ﺳـﺮﻋﺖ ﺑ ﯿﺸـﺘﺮ ي داﺷـﺘﻪ اﺳﺖ. اﯾﻦ ﭘﮋوﻫﺶ ﺑﺎ ﻫﺪف ﺗﺨﻤﯿﻦ زﯾﺴﺖﭘﺬﯾﺮي، ﺑﺎ درﻧﻈﺮﮔﺮﻓﺘﻦ ﻋﻮاﻣﻞ ﻣﺮﺗﺒﻂ ﺑﺎ ﻣﺘﻐﯿﺮ ﺣـﺲ ﺗﻌﻠـﻖ ﺑـﻪ ﻣﮑـﺎن در ﻣﻨﻄﻘﮥ 1 ﺷﻬﺮ ﺗﻬﺮان اﻧﺠﺎم ﺷﺪه اﺳﺖ. در اﯾﻦ ﺧﺼﻮص، ﯾﮏ ﻣﺪل ﺗﺨﻤﯿﻦﮔﺮ ﺟﺪﯾﺪ ﺑﺎ ﺗﺮﮐﯿﺐ ﺳﯿﺴﺘﻢ اﺳﺘﻨﺘﺎج ﻓـﺎز ي ﺗﻄﺒﯿﻖ ﯾﺎﻓﺘﻪ و ژﻧﺘﯿﮏ اﻟﮕﻮرﯾﺘﻢ ﺗﻬﯿﻪ ﺷﺪه اﺳﺖ. ﺑﺮاي اﯾﻦ ﻣﻨﻈﻮر، ﻣﺘﻐﯿﺮﻫﺎي ﻣﺒﺘﻨﯽ ﺑﺮ ﺣﺲ ﺗﻌﻠـﻖ ﺑـﻪ ﻣﮑـﺎن ﺷـﺎﻣﻞ ﮐﺎﻟﺒﺪ، ﻣﻌﻨﺎ، ﻓﻌﺎﻟﯿﺖ، ﺳﺮﻣﺎﯾﮥ اﺟﺘﻤﺎﻋﯽ، ﺣﺲ ﻣﮑﺎن و ﮐﯿﻔﯿﺖ زﻧﺪﮔﯽ ﺑﻪ ﻋﻨﻮان ﻣﺘﻐﯿﺮﻫﺎي ﺗﺨﻤﯿﻦﮔﺮ اﺳﺘﻔﺎده ﺷﺪه اﺳﺖ. ﻧﺘﺎﯾﺞ ﻧﺸﺎن داد ﻣﺪل ﺳﯿﺴﺘﻢ اﺳﺘﻨﺘﺎج ﻓﺎزي ﺗﻄﺒﯿﻖﯾﺎﻓﺘﮥ ژﻧﺘﯿﮏ ﺷﺎﻣﻞ ﻫﻤﮥ ﻣﺘﻐﯿﺮﻫـﺎ ي ورودي )0/926=R(، ﺑﻬﺘـﺮ ﯾﻦ ﻣﺪل ﺗﺨﻤﯿﻦﮔﺮ زﯾﺴﺖﭘﺬﯾﺮي اﺳﺖ. ﻫﻤﭽﻨﯿﻦ ﺷﺎﺧﺺ ﺳﺮﻣﺎﯾﮥ اﺟﺘﻤﺎﻋﯽ ﺗﺄﺛﯿﺮ ﺑﺴـ ﯿﺎر ﮐﻤـ ﯽ در زﯾﺴـﺖ ﭘـﺬ ﯾﺮي دارد. اﻫﻤﯿﺖ ﺷﺎﺧﺺ ﮐﯿﻔﯿﺖ زﻧﺪﮔﯽ ذﻫﻨﯽ ﺑﻪ ﻃﻮر ﻣﻌﻨﺎدارﺗﺮي از ﺳﺎﯾﺮ ﺷﺎﺧﺺ ﻫﺎ ﺑﯿﺸﺘﺮ اﺳﺖ و ﻣﯽ ﺗﻮاﻧـﺪ ﺑﯿﺸـﺘﺮ از ﺳـﺎ ﯾﺮ ﻋﻮاﻣﻞ ﺑﻪ ﺑﻬﺒﻮد زﯾﺴﺖﭘﺬﯾﺮي ﻣﻨﺎﻃﻖ ﻣﻨﺠﺮ ﺷﻮد.

In the last few decades, a decreasing trend is observed in livability of cities due to growth of technology and applying the modernity concept in the construction of cities, which causes the adverse effects on urban spaces. One of the most prominent of these effects, which can be called urban damage, is the decline of values associated with the sense of place in the formation of these spaces. This concern is especially highlighted in metropolises where technology has naturally grown faster. This study provides a framework to estimate the livability in Tehran metropolitan district 1 by considering the sense of place factors. In this way, a novel predictive model is developed based on the integration of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Genetic Algorithm (GA). To this end, several variables based on the sense of place including physical body, meaning, activity, social capital, sense of place, and mental quality of life are considered as predictive variables. Results indicate that the ANFIS-GA model (R=0.926) is the most accurate predictive model when all input parameters are included. Besides, the social capital index has very little effect on livability and the importance of mental quality of life index is more significantly than other indices and can lead to more improvements in livability of regions than other factors.