Informal Settlement Mapping

Informal settlements are home to the most socially and economically vulnerable people on the planet. However, there is very little data available on them, and where there is, it is often incomplete.

Informal settlement detection is very important for census, as it has an important human health benefit. If informal settlements do not appear on maps, they can miss out on vaccinations and other healthcare, for example during Ebola, as well as economic and social aid.

Satellite data has emerged as a powerful tool for mapping and monitoring these settlements, offering several advantages over traditional methods.

Methods of Informal Settlement Mapping:

• Visual Interpretation: Analysts manually examine satellite images to identify informal settlements based on visual characteristics such as building density, irregular street patterns, and the presence of temporary structures.
• Automated Classification: Machine learning algorithms and image processing techniques are used to automatically classify areas into different land use categories, including informal settlements. These methods can analyse large datasets quickly and with consistent accuracy.
• Change Detection: By comparing satellite images taken at different times, changes in informal settlements can be detected. This is useful for monitoring expansion, densification, and redevelopment over time.
• Integration with Other Data Sources: Satellite data can be combined with other geospatial data, such as demographic information, infrastructure maps, and socio-economic surveys, to provide a more comprehensive understanding of informal settlements.