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Geo-spatial mapping in slums

Geo-spatial Mapping of Health Services in Slums

Many of the world’s poorest people live in slums, over-crowded neighbourhoods often made up of makeshift or derelict housing, without running water or sanitation.

Today, slums house nearly a billion people and are growing, as more and more people are born and move to cities. People living in slums have many of the health issues seen in the rural poor (dangerous childbirth, malnutrition, infectious disease deaths) alongside increasing risk of diseases linked to cities (traffic accidents, violence, stroke, heart disease).

Improving health services in slums would have a large impact on health in low and middle income countries. Because slums are overcrowded, better health services could benefit many people at once.

By working collaboratively with multiple stakeholders, the NIHR Global Health Research Unit on Improving Health in Slums hopes to benefit the population of low and middle income countries (LMICs) by reducing morbidity and mortality at the population level.


Researchers now have access to very high-resolution satellite imagery. This imagery is increasingly being used for slum mapping. However, current methods are not capable of a fully automatic identification of slums at a global level. This is due to limited contextual knowledge, the diversity of slums across the globe and difficulties in capturing slum dynamics.

To combat this, humanitarian and pro-poor organisations have been using methods for slum mapping based on crowdsourcing and Volunteered Geographic Information platforms, such as OpenStreetMap. These use data from volunteers to map local areas.

We can produce accurate geographic data by using volunteer data alongside optical satellite imagery. This improved understanding of the geography of slums helps with detailed spatial analysis of the current provision of healthcare services.

Project Objectives

The project aims to map current health services and facilities, and understand how these are used by people living in seven slums across Africa and Asia.

  • Produce accurate maps of slums through the combination of digitisation of Earth Observation satellite imagery and volunteer mapping
  • Map geo-spatially health care service provision for slum residents and identify accessibility patterns

The project will deliver the following outputs:

  • Accurate geo-spatial data about each of the slum sites. This will be stored on the OpenStreetMap database with open access for other organisations
  • Detailed mapping of current healthcare services used by residents and accessibility metrics for the seven slum sites
  • Integrated geospatial database of maps and survey results which can be analysed
  • Printed maps of slums to be used in workshops with local residents, planners and other policy makers