عنوان مقاله [English]
The history of the urban density problem dates back to the ancient cities. In recent decades, the rapid growth and horizontal expansion of the cities of most countries in the world, both developed and developing, has encountered serious problems. Therefore, attention to the concept of space is important in statistical studies. If this factor is ignored in the numerical and statistical information of the research, the results will be error-prone. The whole city is built in space. 3D space is a great way to improve our quality of life. Today, urban density policies in the urban spatial structure are mainly influenced by the financial benefits of floor area ratio and so the spatial dimension is ignored.
The analysis of floor area ratio as a determinant and effective factor in urban planning and the recognition of factors that encourage or inhibit it, is a useful way to solve many of the problems caused by floor area ratio in new cities. In most cases, there is a different relationship between the dependent and independent variables because of their dependence on location. Previous research is more limited to providing maps of floor area ratio that is very general and limited to analyzing the linear relationship between independent and dependent variables, while the maps derived from the proposed model of this study are based on considering the spatial aspects of data that is more accurate and more closely related to reality, and therefore is more reliable. Therefore, the need to pay more attention to the understanding and analysis of urban phenomena affected by the space factor in planning urban design is essential. Therefore, it is important to study the factors affecting floor area ratio and how to apply this effect. In studies of the recognition of these relationships, numerical and statistical information was often used. Among the statistical methods, Geographically Weighted Regression (GWR) is more precise and real to explore the relationship between dependent and independent variables by considering the location. In this field of study, with emphasis on the use of Geographically Weighted Regression software, was presented by Fotheringham, Brunsdon and Charlton of UK University of Science professors. Geographically Weighted Regression method has various uses, including the detection and analysis of variables on a local scale, and has been used in areas such as urban and regional planning, geology, geography, Geometrics and etc. Most studies outside Iran have focused on the relationship between environmental and physical components, and in particular land-use changes, and it can be said that the role of socioeconomic dimensions in this research group is less colorful.
So in this research tries to analyze the relationship between socio-economic factors with floor area ratio as dependent variable with GWR and to explain it more precise than classical methods. The methodology of this study is quantitative. After explaining the studied approach (Geographically Weighted Regression), the concept of floor area ratio and the factors that influence it, the amount of Floor Area Ratio with use of GWR’s method in Takhti neighborhood (Zone 12 of Tehran) with some socio-economic variables such as population density, level of education, land prices, area of urban blocks, number of floors and social security in the neighborhood have been predicted. The result of this study can emphasize the efficiency and accuracy of GWR, while representing the difference between the effectiveness of each of the studied independent variables ( such as land prices, population density, the gross ratio of educated and uneducated people, the area of the urban block, Number of floors, Social Security), on floor area ratio in different geographic coordinates. The influence of these factors on floor area ratio with regard to the location is variable and can change; also it leads to a more accurate perception of urban phenomenon which are influenced by location in urban planning and urban design. Finally, suggestions are made:
• Prioritizing urban planning activities based on the use of later-dimensional research that has less error, and therefore leads to more accurate analyzes and results.
• Provision of floor area ratio criteria in order to promote social security on the eastern edge of Takhti Street according to the resulting map.
• Increasing the number of independent variables in order to increase the accuracy and efficiency of the model.
• The necessity of economical estimation of the location of proposed projects or land use change in the main axis of Takhti neighborhood in accordance with the output map of geographically weighted regression.
Adabkhah, M., Pourjafar, M., & Taghvaei, A. (2003). The Study of the Floor Area Ratio and the Proposed Model of F.A.R Determination According to the Road Network. Honar-Ha-Ye-Ziba Journal, 13, 16-31.
Azizi, M. (1997). Concentration in Urban Designs, A Theoretical View in Identifying Factors and Results. HONAR-HA-YE-ZIBA Journal, 2, 24-32.
Azizi, M., & Arasteh, M. (2011). Explaining Concept of Urban Sprawl based on and Floor Area Ratio. Hoviatshahr Journal, 8, 5-15.
Azizi, M., & Moeini, M. (2010). Analysis of the Relationship between Environmental Quality and Floor Area Ratio. HONAR-HA-YE-ZIBA Journal, 45, 5-16.
Brunsdon, CH., Grose, D., & Harris, R. (2009). Introduction to Geographically Weighted Regression (GWR) and to Grid Enabled GWR. Lancaster University.
Cao, G., Shi, Q., & Liu, T. (2016). An Integrated Model of Urban Spatial Structure: Insights from the Distribution of Floor Area Ratio in a Chinese City. Applied Geography, 75, 116-126.
Erfanian, M., HosseinKhah, M., & Alijanpour, A. (2013). Introduction to Multivariate Regression Methods of OLS and GWR in Spatial Modeling of Land Use Effects on Water Quality. Scientific and Review Journal of Watershed Management, 1, 33-39.
Ghadami, M., & Newman, P. (2017). Spatial Consequences of Urban Densification Policy: Floor-to-area Ratio Policy in Tehran. Iran Environment and Planning B: Urban Analytics and City Science, 1-22.
Hedman, R., & Jaszewski, A. (1991). Fundamentals of Urban Design. (R. Rezazadeh, & M. Abbaszadegan, Trans.). Science and Technology University, Tehran.
Mashhoudi, S. (2010). Building & Urban Congestion in Cities. Tehran: Mazinani Publisher.
Meiss, P., & Ayvazyan, S. (2004). De la Forme au Lieu = Elements of Architecture: from Form to Place. Tehran University.
Moazen Jamshidi, H., Moghimi, M., & Akbari, N. (2011). The Analysis of the Effect of Government Size on HDI in OIC Countries: GWR Approach. Urban- Regional Studies and Research Journal, 8, 95-116.
Official Municipality Portal of the 12th District of Tehran. (2018). District 12 of Tehran. Available at www.region12.tehran.ir.
Shole, M. (2008). Explaining Concept of Congestion as a Means of Urbanization in Housing Designs. Urban Management Journal, 21, 35-45.
Soltani, A., Ahmadian, A., & Esmaeli Ayuki, Y. (2010). Application of Spatial Weight Regression Model in Investigating Relationships between Space Variables in Urban Area. Armanshahr Architecture & Urban Planning Journal, 4, 99-110.
Wu, Y. (2002). Density, Floor Area Ratio and the Newly Developing Residential Districts in Urban Shanghai. A Thesis Presented for the Degree of Doctor of Design Program, Graduate School of Design Harvard University Cambridge.