Data collected about cities, towns, and built-up areas, including demographics, economics, housing, and infrastructure.

Data that can be measured and expressed numerically, used to describe trends and patterns.

Process of collecting data about population and housing, conducted regularly by governments for planning and policy-making.

Separation of racial/ethnic groups into different residential areas, often caused by housing discrimination and economic inequality.

Descriptive data that cannot be measured numerically, used to understand experiences, perspectives, and feelings.

Observing and collecting data in person, including interviews, surveys, and observations, to understand the context of a place or issue.

The process of designing and managing the physical growth and development of cities and urban areas.

Statistical data about the characteristics of a population, such as age, gender, race, and income.

The process of examining geographic patterns to identify relationships, associations, or clusters.

Urban development that meets the needs of the present without compromising the ability of future generations to meet their own needs.

Causes: housing discrimination, economic inequality, personal preferences. Effects: unequal access to resources, limited opportunities, social isolation.

Causes: economic opportunities, migration, population growth. Effects: increased population density, environmental degradation, social changes.

Causes: increased mobility, economic development, reduced congestion. Effects: increased property values, displacement, environmental impacts.

Causes: hurricanes, earthquakes, floods. Effects: displacement, infrastructure damage, economic losses, social disruption.

Causes: economic growth, investment, urban renewal. Effects: gentrification, displacement, increased property values, infrastructure improvements.

Causes: investment in urban areas, increased demand for housing, changing demographics. Effects: displacement of low-income residents, increased property values, cultural changes.

Causes: population growth, car dependency, affordable housing. Effects: increased traffic, environmental degradation, loss of farmland, social isolation.

Causes: lack of access to education, job opportunities, discrimination. Effects: poverty, crime, social unrest, health disparities.

Causes: greenhouse gas emissions, deforestation, industrialization. Effects: sea-level rise, extreme weather events, heat waves, water scarcity.

Causes: lack of social connections, mobility limitations, poverty. Effects: mental health issues, reduced community engagement, increased crime.

Cornerstone of urban planning and policy, helps governments understand population needs and allocate resources.

Crucial for addressing inequality and promoting inclusive communities by understanding separation patterns.

Provides rich, detailed insights into complex issues, exploring nuances and context often missed by quantitative methods.

Provides a more comprehensive and nuanced understanding of urban areas and their complexities.

Maps show distribution of features, patterns of land use, or flow of people/goods, helping understand spatial relationships.

Help understand the context and complexities of urban issues by observing and collecting data in real-world settings.

Urban data informs critical decisions about housing, transportation, economic development, and environmental management.

The measurement of how well a city is functioning in terms of its economy, environment, and social well-being.

Data is used to monitor and evaluate the effectiveness of policies and initiatives aimed at promoting sustainability in urban areas.

Quantitative data may not capture the nuances and complexities of human experiences and social dynamics in urban areas.