Where the Movement Stays
I. Data Scape Parking Space 2006-2020

Ausstellungsprojekt bei ZER01NE DAY 2021
@ alte Hyundai motors Wonhyoro Reparaturzentrum in Seoul
@ SOMA 300 in Berlin

Städtebau / Objekt
Zusammenarbeit mit Astrid Busch(Künstlerin), Keamhwa Kim(Keum Art Projects, Kuratorin)
Team: Changki Kim, Nayun Kim
2021

TEXT in EN

The intersection of informational and sensory approaches on mobility
Ki Jun Kim aims to express the progress and change of the mobility concept in the city through cross viewing urban mobility in Seoul and Berlin. The development of mobility in terms of aesthetic and functional perspectives means a “faster A to B.” However, from the perspectives of urban space and society, better mobility can be understood as a “means for more possibilities to remain in desired territories.”
Mobility means ways of transportation, and as ways of transportation increase, parking lots play a crucial role as places where cars—the means of mobility—depart and arrive. As cities develop and mobility increases, parking lots occupy larger spaces in the city, but at the same time, they reveal an inefficient use of space—being emptied more than half of the day. The 〈Where the movement stays〉 project, started from these clues, exhibits a 3-D data scape which analyzes the size of parking lots, the amount of movement, and the speeds near parking lots in city centers, and provides in-depth interviews on various types of mobility in the daily lives of citizens living in Seoul and Berlin. 〈Where the movement stays〉 demonstrates Ki Jun Kim’s philosophy of “move to stay well,” which is accompanied by Kim's personal experience and thoughts on the modern nomad concept and portrays aspects of the ideal and the reality of lives reflected through mobility in 2021.
The exhibition consists of two parts. Datascape Parking 2006-2020 is a spatial interpretation of urban parking data and textures in collaboration with German (contemporary art) artist Astrid Busch. Mobility x Space, Berlin x Seoul attempts to define new concepts and relationships in terms of social and urban architecture by comparing the past and present of urban space for mobility in Berlin and Seoul.

I. DATA SCAPE PARKING SPACE 2006-2020

Since the mid-20th century, the tremendous increase in demand for private cars fundamentally changed the social and urban structure of the city from road systems to the spatial characteristics of every corner of the city, such as street scenery and the lower part of buildings. In urban context, the most substantial difference between private cars and transportation from the past, such as railways and ships, is that cars do not need large-scale stations or terminals, but at least 2.5 meters x 5.0 meters x 2.5 meters of parking space. As of 2020, the average number of cars registered per person in Korea is 0.5, and it arithmetically means that at least 50 million parking spaces which is equivalent of 156,250 hectares land are in need nationwide. In a more personalized and voluntary trend of mobility, parking spaces in the city will play an increasingly important role as variables and constants in shaping a life of tomorrow.
In order to connect with parking spaces, quantitative and qualitative analysis of Seoul's mobility data, such as traffic volume and average travel speed, was conducted from 2006 to 2020. The mobility tendency revealed in the analysis are embodied by the interactive web, and the interconnection structure and variation characteristics of the data are depicted intuitively and metaphorically through images of space with light and texture. Through this analysis and the sensory experience of spatialized datascapes, we hope to intuitively understand the attributes and relationships between the flow and the stay of people in the city, which we can’t witness right in front of our eyes.

A. Spatial implementation of the relationship of mobility data
Through this analysis and the sensory experience of spatialized datascapes, we hope to intuitively understand the attributes and relationships between the flow and the stay of people in the city, which we can’t witness right in front of our eyes.

B. Aspects of parking space data
The parking area in Seoul is increasing every year. This is to accommodate increasing number of cars by average 0.72 % annually. As parking lot area increases every year, the secured parking rate increases by 2.2 percent. The area of parking lots in Eunpyeong-gu has the highest rate of increase, and Mapo-gu, Gangseo-gu, Songpa-gu, and Seongbuk-gu follow in order. *the secured parking rate = (Parking lot area/The number of registered car) *100

C. Correlation between parking space and average moving speed data
The average annual traffic speed in Seoul is decreasing every year. The number of parking lots is one of the main reasons for this. As the number of parking lots increases in each autonomous district and the capacity of vehicles increases, the speed of vehicles has significantly decreased in five other districts besides of Nowon-gu. In Nowon-gu, Dobong-gu, Yeongdeungpo-gu, Seongdong-gu, Gangseo-gu, and Yangcheon-gu (r index above 0.8), the speed of vehicles and the secured parking rate also have a close relationship to each other. In addition to Nowon-gu and 11 other districts, the speed of cars decreased as the secured parking rate increased.
* Correlation coefficient r refers to a measure of quantifying the degree of linear relationship between two variables. r has values from -1 to +1, and the weaker the correlation between the two variables, the closer it is to 0. The closer the r value is to +1, the more correlated the two variables are, and both variable values tend to increase. On the other hand, the closer the r value is to -1, the less correlated the two variables are, and the value of the one variable decreases, the more likely the value of the other increases.

D. Aspects of traffic data
In 2012, the average daily traffic volume in Seoul increased by 42.3 percent from the previous year. The main reason is that data for each point of the arterial road begins in 2012 in the process of integrating traffic by city point, boundary point, bridge point, and arterial road point. Even when each of the four traffic data sets was observed, there were some districts that lack the traffic volume by year. It is important to note that the reliability of the results of the correlation between the singularity of the traffic change in time series and other factors decreases relatively after data processing of analyzing the 15 years of time series.

E. Complexity of data correlation
The parking area per district, vehicle speed, and traffic volume don’t necessarily show consistent functional relationships. This is because various variables such as traffic conditions in neighboring Gyeonggi Province coexist as well as the connection between districts. Songpa-gu is the only autonomous district where these three data are statistically related to each other. As the number of parking area increases, the traffic volume also grows with, while vehicle traffic reduces.

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ZER01NE Projekt

Ausstellung @ SOMA 300 1

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