Dataset of global cities' congestion level and urban spatial pattern

Area of Science:

• Urban Studies
• Urban Planning
• Geographic Information Science

Background:

• Global cities face complex challenges including traffic congestion and varying urban development.
• Understanding urban spatial structure and population dynamics is crucial for city planning and policy-making.
• Historical events, such as World War II, can have lasting impacts on urban landscapes.

Purpose of the Study:

• To compile a comprehensive dataset of global city indicators.
• To provide data for analyzing urban spatial structure, congestion, and population.
• To offer a reusable dataset for various urban-related research analyses.

Main Methods:

• Congestion data sourced from TOMTOM, including various metrics from 2004 and 2020.
• Skyscraper index calculated based on building height data (buildings > 150m) from the Council on Tall Buildings and Urban Habitat.
• WWII bombing data compiled as a dummy variable (1 if bombed, 0 otherwise) from historical records.
• Global city population, area, and density data collected from official city or country statistics departments.

Main Results:

• The dataset integrates diverse urban metrics, offering a multi-faceted view of global cities.
• Key variables include congestion levels, skyscraper density, WWII impact, and population figures.
• The data allows for the examination of relationships between urban form, population, and historical context.

Conclusions:

• This dataset serves as a valuable resource for researchers studying urban dynamics and global city characteristics.
• The integrated indicators facilitate comparative analyses of urban development and resilience.
• The data's reusability supports diverse research questions in urban planning and social sciences.