Analysis of the streets which are important for the urban image with fractal geometry

Streets, which are considered as an important urban space in terms of urban identity, affect people's perceptions thanks to their physical, spatial, functional, formal, historical, cultural, social, and visual features. When people's perception of the street is negative, the intelligibility of the street and the city is also low. This situation makes it difficult for the city to be resolved. Perception forms the basis of the relationship between human and place. The clear perception of the streets also positively affects the image and the identity of the city. In the study, perceptible places were evaluated using the fractal geometry and recognition test method. The street-scale study provides an analysis of the spatial richness of 46 streets selected from the cities of Istanbul and Ankara. The differentiation of physical qualities was determinant in the selection of the streets as the sampling area. Firstly, the fractal dimensions of the street images were calculated with the help of the HarFa program, and the relationship between the obtained values and physical properties was examined by correlation analysis. As a result of this analysis, it was determined that the density of the building facades, the number of buildings with different aspect arrangements, the density of the reinforcement elements, the width of the street, the rate of closure, the total number of buildings and the density of the landscape elements have statistically significant effects on the fractal dimension. Then, spatial perception assessment was made with 170 participants using the recognition test method. As a result of the test, it was stated that building aspects, street width, and the density of reinforcement elements are more effective in recognizing streets than other qualities. A correlation analysis was performed again between the recognition rates of the streets and their fractal dimension values. As a result of the analysis, it was determined that as the recognition rate of streets increased, their fractal dimension increased. Finally, suggestions were developed to increase the perception of urban space by evaluating all findings obtained.