Project Summary

Drone flights enable studying any aggregations of waste/informal dumps that are on the banks of the waterways within fifty metres of its bank on either side. Such data is presented as three-dimensional imagery of waste aggregations, further assisting the study team to estimate rough waste volumes.

Drone flights consistently track and record spatial data relating to their own trips and correspond the GIS data with a set of other socio-political and economic indicators, to ease further analysis. This includes


  • The corresponding political division i.e. subward, ward, and municipal boundaries—drone flight spatial data overlaid existing socio – political spatial data indicating, via simple desktop analysis, the political constituency that governs each spatial area the drone covers. This allows users to correspond with an informal/illegal dump with the relevant political office that governs the area.
  • The corresponding density of the geography they are flown over i.e. buildings per sq km/population per sq km via census data. 

OMDTZ combined drone flights and the existing spatial data to conduct a rapid desktop analysis of planned residential and commercial zoning and transport economics as they relate to solid waste management services. Specifically, the spatial analysis allowed the team to quickly present:


  • Any building or point on a map within the political boundaries of Dar es Salaam that are defined as planned or unplanned.
  • The complexity of transport from any building in Dar es Salaam to Pugu Kinyamwezi dumpsite–accounting for two-axle vehicle access, road surface and type, distance, and time.     

Datasets provided audiences with vital data on the inequality of solid waste management infrastructure by geography, as well as providing service providers and government with valuable data on what types of transport modes can be employed to service residents and businesses in planned and unplanned geographies of the city.

Thereafter, OpenDataKit (ODK) Collect, Kobo Toolbox, and QGIS training were provided to Nipe Fagio staff. OMDTZ provided in-depth training on how to upload, analyze, and present visual data relating to waste hotpots, informal dumps, and cleaning activities.

OMDTZ in collaboration with i4ID also conducted training to ilala municipality on how they can make use of these data towards a clean city.


Project Timeline

Project Time

The project was implemented between March to June 2019

Funding Partners

The project was funded by the Palladium Group and implemented by OMDTZ and Uhuru Labs, while the primary beneficiaries of the project were Nipe Fagio and i4ID






Palladium Group



Featured pictures

Impact of the Project​

Data Set

Provided datasets that will support city waste management including trash collection

Improving Inflastructure

Created the best routes to transport detected piles of waste to the main dumping site, and clearly show the inequality in waste management basing on geographical locations and infrastructure gap