In Tandale producing a street map (streets, paths and points of interest) isn’t enough. Enriching the dataset and publishing allows for extra dimensions to be added to the environment. From the community forum and interaction with the holistic community we have identified the following themes to be mapped…
Health (Medical facilities; both formal and informal and pharmacies)
Water (Public/private water sources, water towers and flood prone areas)
Education (Schools, madrassas)
The above is a good start and will present us with many miles of surveying to be covered. We also have a secret weapon; Satellite Imagery. The good people at Bing opened up their satellite imagery for usage in OSM. This means we can trace building outlines and identify landuse.
It is difficult to identity landuse purely from the satellite imagery – the resolution for Dar Es Salaam is around 1-2m; it’s good but not perfect. However with an on the ground survey taking place we make a waypoint for the landuse (be it an ODA, economic or commercial zone) then use the imagery to demarcate the area which is covered by the landuse. An area where you can see the effect of this is the Mharitan subward where the residential and industrial landuse have been demarcated.
Our further aims will be to identify the retail (convenience stores, butchers, kiosks) and commercial (markets and places for commercial goods ) landuse areas. Instances where individual kiosks and shops are embedded in residential areas won’t change the landuse, instead it will be about approximating landuse.
Residential landuse in a western sense is very much focused on parcels of land where people live. In Tandale and broadly across East Africa the entreprenural spirit is strong, as such you often find residents making chapatis or selling nuts or single use, packet goods out of their front doors. This doesn’t mean that these areas are quasi-retail it means that people are doing what they can to live.
Combing satellite imagery to get concise building outlines with landuse data we can then add the population data from the census. With this average household sizes can then be approximated. Then the identification of access to water, education, sanitation and health per x of population can be extrapolated. The precision isn’t as good as it could be, but providing a baseline is beneficial for the measuring the impact of future service provision.
The dynamism of the underlying population means that accurate statistics are hard to come by, however this is an issue of censuses anywhere not just in developing nations like Tanzania.
Our way forward will be to produce accurate building outlines and a landuse survey with the themes mentioned above. No wonder we’re working weekends as well!
Written and submitted from the Hotel Kilimanjaro, Dar Es Salaam ( -6.8173, 39.2931)