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

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.