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Large cities like Nairobi and Mombasa are characterised by the existence of large urban slums. Many of these slums are made up of several “villages”. These villages are usually recognized by the residents of those settlements, by way of their names and sometimes their unique characteristics. Some of these villages bear funny names, which refer to some events that took place or a prominent personality or activity (legal or illegal) that goes on in the neighbourhood. The dense population of these villages/areas and their obvious distinction from one another has made the administration to allow such villages/areas to have village elders to support the administration. The village elders also know the boundaries of their respective villages/areas.
Within slums that consist of several villages the village was adopted as the mapping unit as well as the unit for group interviews. Usually, the identification of the villages was carried out during a consultative meeting, the main participants being the area (Assistant) chief(s) and the village elders. A physical appraisal normally followed the consultative meeting and was meant to enable the mapping team to familiarise themselves with the villages.
Only where, in the opinion of the mapping team, a particular village was very small in size and the population seemed low, the village was merged with the adjacent one. The final name recorded in the data sheets reflected the merger. This approach ensured that in spite of the complexity of large settlements/slums, the appropriate mapping unit was selected.
The nature of physical planning in Kenya, which has seen sprawling of urban areas even in areas which were once restricted for agricultural purpose, presents a challenge in defining the limits of urban resident areas from the rural areas. This normally is the case especially along the major highways where extension of urban setting continues unchecked as a strip sometimes to the edge of the next town.
Since the MajiData mapping exercise targeted the urban low income areas, the need emerged to be able to classify areas as being rural or urban. The decision was made to use criteria such as population size and density, expected population growth (urban development) and urban or rural characteristics (e.g. farming being the main livelihood activity). If the population density exceeds 400 persons/km2 MajiData classifies an area as urban on the basis that rural water supply solutions (e.g. hand pumps and rainwater harvesting) can no longer be regarded as sources of safe water.
Adopting the above-mentioned criteria implies that the MajiData team when separating rural from urban adopted an area and population density focus instead of being guided by for instance administrative boundaries.