In what ways can urban poverty be mapped?

Urban poverty can be mapped using geographic information systems (GIS), census data, satellite imagery, and participatory mapping.

Geographic Information Systems (GIS) is a powerful tool that can be used to map urban poverty. GIS allows for the visualisation and analysis of spatial data, which can be used to identify patterns and trends in poverty. For example, GIS can be used to map the distribution of income, employment, education, and health services in a city, which can help to identify areas of high poverty. Additionally, GIS can be used to map the physical characteristics of a city, such as housing quality and access to basic services, which can also indicate areas of poverty.

Census data is another important source of information for mapping urban poverty. Census data provides detailed information on the socio-economic characteristics of a population, such as income, employment, education, and housing. This data can be used to identify areas of high poverty and to understand the underlying causes of poverty. For example, if census data shows that a particular area has a high unemployment rate and low levels of education, this could indicate a high level of poverty in that area.

Satellite imagery can also be used to map urban poverty. Satellite images can provide a bird's eye view of a city, which can be used to identify areas of informal settlements or slums, which are often associated with high levels of poverty. Satellite imagery can also be used to identify areas of poor housing quality, lack of basic services, and environmental hazards, which can all indicate areas of poverty.

Participatory mapping is a more bottom-up approach to mapping urban poverty. This involves working with local communities to map their own experiences and perceptions of poverty. Participatory mapping can provide a more nuanced understanding of poverty, as it takes into account the local context and the lived experiences of people in poverty. For example, participatory mapping might reveal that a particular area is considered poor not just because of low income, but also because of factors such as crime, lack of social cohesion, and poor access to services.