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[042] Operationalizing Kevin Lynch's the City Image Elements on Urban Vibrancy
Keywords:the image of city, imageability, urban vibrancy, big data
This study operationalizes Kevin Lynch’s the city image elements on urban vibrancy. Kevin Lynch defined ‘Imageability’ as quality of the city that in an object which gives it a high probability of evoking a strong image in the observer (Lynch, 1960). High imageability will offer a sense of emotional security and the intensity of human experiences. To figure it out, Lynch drew mental map with five city image elements based on field survey. Those five distinct elements are paths, edges, districts, nodes, and landmarks. Those elements have different dimensions and are non-static and interrelated. However, as he criticized himself, his method to figure out the city image elements have some limitations. First, it can be biased by small number of surveys. Second, those manual methods were inadequate to get a true mental image (Lynch, 1995). Third, there is observer variation which means people has different backgrounds and experience (Carmona et al., 2003).
To overcome such limitations, recent studies figured out various urban features that represents the city image elements using urban big data. Social network data was analyzed to get how people subjectively depicts the city image elements and how it implies the city image (Jaio et al., 2018; Huang et al., 2021). Geographic information system concluding street network, facilities and more was used to digitalize the city image elements (Filomena et al., 2019; Lee et al., 2019). However, those studies only figured out the city image elements and did not empirically verified its operation.
This study measures the effect of the city image elements to operationalize them on urban vibrancy. Urban vibrancy promotes human activity and interaction and is a one of the vital elements used in assessing city quality (Jacobs, 1961; Yuan and Han, 2019). Following its implication, the city image element and urban vibrancy are suggested to have a relation. The city image elements in Seoul will be obtained by unit of dong, the smallest administrative unit in Seoul, using various urban geographic and social data. As the city image elements makes imageability higher, it will operate urban vibrancy.
This study contributes an understanding and modernizing the city image elements and operationalizing them on urban vibrancy. This empirical study should provide important policy implications for Seoul.
To overcome such limitations, recent studies figured out various urban features that represents the city image elements using urban big data. Social network data was analyzed to get how people subjectively depicts the city image elements and how it implies the city image (Jaio et al., 2018; Huang et al., 2021). Geographic information system concluding street network, facilities and more was used to digitalize the city image elements (Filomena et al., 2019; Lee et al., 2019). However, those studies only figured out the city image elements and did not empirically verified its operation.
This study measures the effect of the city image elements to operationalize them on urban vibrancy. Urban vibrancy promotes human activity and interaction and is a one of the vital elements used in assessing city quality (Jacobs, 1961; Yuan and Han, 2019). Following its implication, the city image element and urban vibrancy are suggested to have a relation. The city image elements in Seoul will be obtained by unit of dong, the smallest administrative unit in Seoul, using various urban geographic and social data. As the city image elements makes imageability higher, it will operate urban vibrancy.
This study contributes an understanding and modernizing the city image elements and operationalizing them on urban vibrancy. This empirical study should provide important policy implications for Seoul.