Dar es Salaam is one of the fastest growing cities in East Africa, with a population of 4,364,541 whose annual growth rate is 4.5%. The population increase is mainly caused by rural to urban migration causing traffic congestion, unemployment, emerging of unplanned settlements, inadequate infrastructure, and social and housing services. In order to overcome these challenges there is an urgent need to establish and determine suitable locations of satellite towns to the outskirts of the central business district (CBD) to strengthen economic and social activities using reliable techniques. Selecting suitable locations of satellite towns has been determined by using distance from the CBD and population growth indicators. The limitations of using these indicators include unsuitable locations, which ultimately failed to attract economic growth in such areas. In this study, we introduce a new approach of selecting suitable location of satellite towns in fast growing cities. This approach uses Saaty Model and Geographic Information Systems techniques, whereby a pair wise comparison matrix, consistency index and consistency ratio are employed to determine suitable locations of satellite towns in Ubungo and Kinondoni Municipalities. Also, seven criteria were used to produce suitability maps for water, power line, road, communication line, elevation, slope and land use. The results obtained from this study show that about 5.31% of the area was classified as highly suitable, 29.82% as moderately suitable, 24.27% as marginally suitable and 40.6% permanently unsuitable. Locations of satellite towns determined using Saaty model was found to be on highly suitable areas whereas locations of satellite towns proposed by the Dar es Salaam master plan were located on marginally suitable areas. The study concludes that Saaty Model, if integrated with GIS, can be effectively used to determine suitable locations for satellite towns in urban areas.
|Journal||Journal of Data Analysis and Information Processing|
|Publication status||Published - 2018|