HOW TO DEFINE A CITY SQUARE? CITY SQUARES : SUGGESTIONS VIA DATA MINING
City squares are one of the most important images reflecting the characteristics, identity and culture of a city. Squares diversify and differ according to the characteristics of the city. Especially in metropolises such as Istanbul, which have a cosmopolitan culture, history and public, the features of the city square also have great variations. For this reason, each square has a different feeling on the user and a feature that enables the specified area to be defined as a square. For example, while the peninsula in Sultan Ahmet Square (Figure 1) feels its mystical feeling and its history deeply, the Taksim Square (Figure 2) symbolizes freedom, a space where people can defend their own ideas and priorities. For example, Yenikapı event square (Figure 3) was established for political gathering, while Üsküdar Square (Figure 4) gained identity with the coexistence of the Bosphorus and history. While some squares are concreted as if we are enemies of green, some squares are famous for their resistance to preserve the green. The combination of all this past, future and present creates differentiated squares and identities. So the initial question is, what are the features that make the square a square?
First, the definitions of city squares were searched. According to Dyer and Ngui (2010), the city square is derived from the Latin word “Platea”, which means open space or extended street, and is born from the word “Place” in English and French. The Spanish “Plaza” and the Italian “Piazza” have the same origin. According to Lewis Mumford (2001), the primary function of a city square is the acculturation and humanization of its inhabitants and for these purposes public spaces are the essential tools in the city. Squares need to have qualities of permeability, legibility, opportunities and robustness to support different purposes (Lynch, 1981; Mossop, 2001). Mossop (2001) suggested that public culture and urban values are expressed in public spaces that encourage people to gather and socialize. Vitality and sociability in public space means that people can carry out their activities in relative comfort and safety while interacting, engaging in spectacles and ceremonies, or just simply sitting or waiting (Jalaladdini & Oktay, 2012; Tibbalds, 2001). Fauole describes the square as empty spaces defined by the designed environment and states that a place must first be pedestrianized in order to be defined as a square. The basic criterion in the design of a square is to increase the quality of the place where that square is built (Fauole 1995). According to Kevin Lynch, squares are intense activity centers created in urban spaces. Typically, squares are paved and surrounded by high density buildings and streets. It has features that affect groups of people and facilitate meetings (Marcus and Francis 1998). Today, squares can be defined as public spaces with hard floors and excluding cars. Its most common uses are to sit, eat and watch (Marcus and Francis 1998). The diagram of the square concepts obtained from the entire literature review is shown in Figure 5.
In line with the literature review and personal experiences, attributes were determined for each city square. Attributes, their definitions and data sources are shown in Figure 6. According to Çakırcıoğlu, Reyhan and Kurt’s (2010) study, 64 squares in Istanbul were determined as instances. The square type separations in the same study were included in the study as an attribute.
DATA ANALYTIC QUESTION
With the increase of the population in metropolises such as Istanbul, construction is increasing. The need for an environment where the city dwellers can stop and rest in the city chaos and do different activities, in this case a city square, is increasing. However, most of the city dwellers in Istanbul complain about the lack of this need. For this reason, parking lots that can easily function under the ground have a great potential for use as squares. For these reasons, the study data analytic question was determined as “Can potential to transform car parks into city squares be guessed with a prediction model?”
DATA ANALYTIC APPLICATIONS
A total of 5 steps were followed in the study. These steps are respectively:
- Defining and creating data set
- Select label ( city square type)
- Experiment mutual information matrix (Figure 7)
- Control the label classification with clustering model (Figure 8)
- Implement prediction model (teach label attribute to ML) (Figure 9) -%50 training set -%50 test set
- Experiment with car park turning into city squares. (application set)
In the study data set, the total number of instances is 64, the number of attributes is 14, and the number of application set instances is 5. The number of city square types selected as a label in the project is 4. City landmark: 18, ceremony / meeting: 8 instances, transportation: 5 instances, culture / commerce: 32 instances is defined.
OUTPUTS — VISUALIZATION / INTERPRETATION of THE RESULTS
Outputs from 3 data analytic models are evaluated in this section. The first application is the mutual matrix. With this study, the relation of the selected label (city square type) with other attributes is examined (Figure 10). According to outputs of the experiment 1, the city square type most associated with: commercial use, different transportation potential, photo popularity ratio. Also, the city square type least associated with pedestrianization.
However, according to my personal opinion, since almost all the squares in the data set are pedestrianized, it was included in the results as the least effective attribute. Similarly, it has been read that the number of landmarks is an attribute in all squares, so it provides little effect in determining square types. The visualization of the data obtained from the outputs of Experiment 1 is included in Figure 11.
As can be seen from the outputs, the Cluster model has also divided the data into 4 classes . However, there are some changes in the classification. When we examine the prominent features of Cluster 1, which has the least number, we can see that it has high popularity, cultural activity and transportation potentials, that is, it has criteria close to the definition of an ideal square. However, when Cluster 3, which has the highest number, is examined, it has a less preferable definition of a square where cultural activities and popularity value are low. With these data, it can be evaluated as an indicator of the need for an ideal square for the urbanites (Figure 12). When we look at the pie charts, Cluster 3 mainly includes the ceremony / meeting type in all types. In addition, Cluster 1 is only available in the city landmark (Figure 13).
As a result of experiment 3, a prediction system with an accuracy of 62.5% was created. Accordingly, 5 underground parking areas selected from Istanbul were predicated. According to the results, culture / commerce and city landmarks were correctly predicted at 77% — 84%. Output has no transportation forecast. This is thought to be due to limited data of this type. A very small rate, the ceremony / meeting is among the predictions. Result estimates vary between culture / commerce and city landmarks. When the data table and outputs are examined, it is estimated that the high-popularity parking lots can be converted into Landmarks. It is classified as culture / commerce in parking lots with high transportation and commercial usage rates (Figure 13).
FUTURE STUDIES
Issues that can be developed within the scope of this study: the data set used in the study is limited, the outputs of the mutual matrix and clustering model could not be read in harmony. For this reason, it is thought that more consistent outputs will be obtained by increasing the data set. An accurate predict model can be obtained by developing the data set. In the model with consistent results, the number of car parks in the application set can be increased and functions appropriate to the context of underground car parking areas in different cities can be provided.
Issues that can be developed within the different scope of this study:
In future studies, by applying the developed base of this study in areas with square potential in the city, which features can be designed a square can be included in the design decision processes. This study has been fictionalized only in the context of the square concept. However, in future studies, a similar system can be followed for touristic streets, avenues and parks that reflect the city’s identity. In future studies, the attribute list may change depending on the context of the study. For example, in a park study, the cultural dynamics of potential users of the park can be associated with attributes. Thus, environments that are unique to the place, that do not break away from the environment and where the city dweller can breathe can be designed.
REFERENCES
Çakırcıoğlu, M., Reyhan, S., Kurt, Timuçin. (2010). İstanbul Meydanları. İstanbul Büyükşehir Belediyesi İmar ve Şehircilik Daire Başkanlığı Şehir Planlama Müdürlüğü.
Dyer, H., Ngui, M. (2010).Watch this Space: Designing, Defending, and Sharing Public Space,
Kids Can Press. page (8–78)
Lynch, K. (1981). A Theory of Good City Form. Cambridge: MIT Press.
Mossop, E. (2001). Public space: Civilising the city. In E. Mossop & P. Walton (Eds.), City Spaces: Art & Design (pp. 10–26). Sydney: Craftsman House.
Das, D. (2008). Urban quality of life: A case study of Guhawati. Social Indicators Research,
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Jalaladdini, S., & Oktay, D. (2012). Urban public spaces and vitality: A socio-spatial analysis in the streets of two Cypriot towns. Procedia — Social and Behavioural Sciences, 35, 665–674.
Khalilah Z., Harun Z & Mansor M. (2014) Spatial Characteristics of Urban Square and Sociability: A review of the City Square, Melbourne
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Fauole, P., 1995. Squares in Contemporary Architecture. Waanders Publishers Architectura & Natura Press, Amsterdam.
Marcus, C. C., Francis, C., 1998. People Places ‘Design Guidelines for Urban Open Space’. Van Nostrand Reinhold Company, New York
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