Research

Urban diversity

In the mid 20th century, Jane Jacobs claimed the following four conditions for the urban vibrancy: (1) mixed use neighborhoods, (2) small blocks, (3) a mix of old and new buildings, and (4) sufficient density of people. However, this statement has not been quantitatively tested over the last decades. Enabled by the fine-grained data sets, we try to quantify the conditions for the urban vibrancy.

Reference: Kumakoshi, Y., Koizumi, H., & Yoshimura, Y. (2021). Diversity and density of urban functions in station areas. Computers, Environment and Urban Systems, 89, 101679. Free download until August 21 2021 from here. Permanent link: https://doi.org/10.1016/j.compenvurbsys.2021.101679

Yoshimura, Y., Kumakoshi, Y., Milardo, S., Santi, P., Murillo Arias, J., Koizumi, H., & Ratti, C. (forthcoming). Revisiting Jane Jacobs: Quantifying urban diversity.

Green View Index

Urban green vegetation or canopy provide shades on the street, mitigation of heat island effect, psychological comfort and so on. However, the presence of the trees has not been well captured. This study employed the Green View Index, an indicator of visibility of greenery at street level, and proposed an area-level estimation of the visibility of green vegetation. First, calculation sites of Green View Index (GVI) were positioned along streets. Second, Google Street View images on these sites were retrieved. Third, the proportion of green pixels was estimated. Forth, hereby estimated GVI was aggregated at area-level, using Voronoi tessellation to consider the network structure in the area. The resultant estimation was robust to the bias from point locations.

More detailed description is available here.

The code for standardized GVI is available on my Github page.

Reference: Kumakoshi, Y., Chan, S. Y., Koizumi, H., Li, X., & Yoshimura, Y. (2020). Standardized green view index and quantification of different metrics of urban green vegetation. Sustainability, 12(18), 7434.

Autonomous vehicles and urban planning

In the advent of autonomous vehicles, which do not necessitate as much parking space as the conventional vehicles, transport planners and urban planners must conceive a new scheme of planning. I developed a simulation combining the operation of Shared Autonomous Vehicles (SAVs) and a dynamic traffic flow simulator, and analyzed the impact of the SAVs on the parking demand and the traffic flow.

Reference: Kumakoshi, Y., Hanabusa, H., & Oguchi, T. (2021). Impacts of shared autonomous vehicles: Tradeoff between parking demand reduction and congestion increase. Transportation Research Interdisciplinary Perspectives, 12, 100482. https://www.sciencedirect.com/science/article/pii/S2590198221001871

Innovation workshop

To explore innovative idea for the uncertain future, typically with the risk of disasters such as earthquakes, we carried out an innovation workshop for policy makers of Isesaki city, Gumma prefecture, JAPAN in October 2020. More detailed information is available here in Japanese.