The Global Urban Observatory (GUO) of UN-HABITAT started in 2003 with the Monitoring Urban Inequities Program (MUIP) and recently a study was completed on Nairobi. The program will strengthen the global monitoring and reporting on goals and targets of the Habitat Agenda (HA) and the Millennium Development Goals, especially on target 11 of the MDG to 'improve significantly the lives of at least 100 million slums dwellers by 2020'.

The GUO has two main functions: to develop a global sample of cities, and to provide support to local policy formulation. A component of the second main functions is to provide GIS technology and training. ITC has seconded a staff member to the UN Habitat GUO to assist in the development of training modules, to conduct training courses, and to provide general GIS support to the project.

The study on intra-city differentials in Nairobi City was using a 5% sample (102,000 people) of the 1999 Housing and Population Census from Kenya and additional data was collected during a survey in 2002 to classify the 4700 Enumeration Areas as slum/non-slum. Quantitative methods were used to analyse the urban poverty issue with a special focus on living conditions within Nairobi, and the output is considered useful to support local policy formulation on poverty alleviation. A Geographical Information System (GIS) was used to visualise the spatial variations of living conditions within the city at sub-location level, which is a spatial unit with an average of 20,000 inhabitants.

One of the objectives of the study is develop and illustrate a methodology for intra-city differentials study using census data, and the use of GIS as a tool to show the spatial variation of urban poverty and poor living conditions within a city.

Within a Population and Housing Census many variables on living conditions such as building materials, access to water and sewerage, etc. are recorded in different classes. These characteristics have been recoded into bad and good quality and later combined and aggregated to develop an index on living conditions at the sub-location level.
The exploratory analysis focussed on the principal component analysis and bi-variate correlation analysis, and used a regression model to identify the correlates of slums, urban and other socio-economic characteristics. The statistical analysis shows that many poverty related factors are spatially clustered and location does impact poverty. What is also significant is that land is unequally distributed as 60% of the population of Nairobi lives on 4490 Ha which equals to 8.7% of the land.

The map on Slum Incidence shows where slum areas are concentrated in Nairobi.