Bongwook Koo
Yonsei University · Environmental Science
About the Lab
Professor Bongwook Koo's research lab specializes in urban environmental data science, focusing on the intersection of urban form, environmental equity, and human well-being. The lab employs advanced technologies such as computer vision, audio sensing, and big data analytics to quantify street-level urban design factors and their impacts on walkability, perceived safety, and environmental justice. Key research directions include the development of scalable methods for measuring urban environments using remote sensing and sensor data, and applying machine learning to support equitable and sustainable urban planning. The lab emphasizes data-driven approaches to address urban challenges such as environmental inequity and pedestrian infrastructure planning.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15The built environment characteristics associated with walkability range from neighborhood-level urban form factors to street-level urban design factors. However, many existing walkability indices are based on neighborhood-level factors and lack consideration for street-level factors. Arguably, this omission is due to the lack of a scalable way to measure them. This paper uses computer vision to quantify street-level factors from street view images in Atlanta, Georgia, USA. Correlation analysis s
While previous studies in environmental equity found positive relationships between tree canopy and socioeconomic/demographic status of neighborhoods, few examined how changes in tree canopy are associated with changes in socioeconomic/demographic status. This study confirms that the relationship between them in Atlanta is changing and the hypothesis of inequitable distribution of tree canopy concerning demographic attributes cannot be fully supported beyond 2000. In addition, the proportion of
The perception of safety significantly influences choices in outdoor activities, profoundly impacting overall well-being. While previous studies have highlighted urban trees’ potential to reduce crime rates, the link between urban trees and perceived safety remains uncertain. This study investigates the relationship between urban trees and safety perception in Austin, Texas, USA, with a specific focus on the moderating role of neighborhood cleanliness and environmental justice considerations. Us
Abstract While various sensors have been deployed to monitor vehicular flows, sensing pedestrian movement is still nascent. Yet walking is a significant mode of travel in many cities, especially those in Europe, Africa, and Asia. Understanding pedestrian volumes and flows is essential for designing safer and more attractive pedestrian infrastructure and for controlling periodic overcrowding. This study discusses a new approach to scale up urban sensing of people with the help of novel audio-base
Introduction Before the COVID-19 pandemic, walkability was linked to improved mental health . However, walkable areas can be more vulnerable to outbreaks of infectious diseases due to increased interaction and proximity between individuals, potentially leading to adverse effects on mental health. Whether walkability maintains its positive association with better mental health during the pandemic remains unclear, especially given mixed findings on whether walkability increases COVID-19 cases. Met
Spatially explicit data about the physical and natural environment are becoming ubiquitous with the growing number of air/space-borne and terrestrial sensors. While this growing volume of data has transformed the operations of various sectors in both private and public domains, such as agriculture, natural resource management, transportation and retail services, the impact on urban spatial planning has been minimal. This chapter discusses the evolving approaches to spatial modelling and forecast
<p>The built environment characteristics associated with walkability range from neighborhood-level urban form factors to street-level urban design factors. However, many existing walkability indices are based on neighborhood-level factors and lack consideration for street-level factors. Arguably, this omission is due to the lack of a scalable way to measure them. This paper uses computer vision to quantify street-level factors from street view images in Atlanta, Georgia, USA. Correlation a
<p>The built environment characteristics associated with walkability range from neighborhood-level urban form factors to street-level urban design factors. However, many existing walkability indices are based on neighborhood-level factors and lack consideration for street-level factors. Arguably, this omission is due to the lack of a scalable way to measure them. This paper uses computer vision to quantify street-level factors from street view images in Atlanta, Georgia, USA. Correlation a
Research Areas
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