The document summarizes a study on using spatial network modeling to help plan sanitation infrastructure in informal settlements. It describes how the researchers used crowd-sourced map data from OpenStreetMap and Map Kibera to build a database and topological network model of the Kibera informal settlement in Nairobi, Kenya. This included locations of roads, paths, public toilets, and potential sites for waste transfer stations. The network model was then analyzed using algorithms to optimize locations of transfer stations to minimize transport time for waste collection vehicles. The results helped identify how sanitation systems could be designed to most efficiently service the needs of people living in informal settlements.

1. ENDORSING PARTNERS
Spatial Network Modelling
for Sanitation Planning in
Informal Settlements
The following are confirmed contributors to the business and policy dialogue in Sydney :
Rick Sawers (National Australia Bank)
Nick Greiner (Chairman (Infrastructure NSW)
Monday, 30th September 2013: Business & policy Dialogue
Tuesday 1 October to Thursday,
Dialogue
3rd
October: Academic and Policy
Presented by: Dr Tomas Holderness SMART Infrastructure Facility,
University of Wollongong
www.isngi.org
www.isngi.org

2. Spatial Network Modelling
K
for Sanitation Planning in
Informal Settlements
Tomas Holderness1, Ruth Kennedy-Walker2, David Alderson2 & Barbara Evans3
1
University of Wollongong, 2 Newcastle University (UK), 3 University of Leeds (UK)

3. The Sanitation Infrastructure Crisis
• Rapid city densification
• Peri-urbanisation growth
• Informal infrastructure
Image credits: [1] Nils Gilman/io9.com; [2] PIUS UTOMI EKPEI/AFP/Getty Images

4. The Sanitation Crisis
Image credits: [1] WHO/UNICEF

5. Critical Infrastructure?
A “frogman” manually
emptying a pit latrine in
Dar es Salaam
Image credits: [1] Florian Erzinger

6. The Solution?
Vacutug:
• Vacuum pump truck
• 0.5m3 capacity
• 5 Km/h speed
Image credits: [1] Rémi Kaup; [2] Sustainable Sanitation Alliance

7. Transfer stations
• Reduce Vacutug travel
time
• Situated at the edge of
informal settlement
• Serviced by large
collection tanker
• Location is key to
reduce time and costs
Image credits: [1] Authors; [2] Tilley et al. 2008

8. A new approach
• Crowd-sourced mapping for spatio-toplogical network modelling
• Land cover, road/path network, amenity location
• Optimise location of transfer stations to minimise transport time
• Iterative, weighted Dijkstra’s algorithm
• Open-source tool to support Engineers in the sanitation planning
process
Image credits: [1] Map Kibera

9. Methodology
Data preprocessing &
spatial database
construction
MCE site analysis
Create network
Network Analysis

10. Data preprocessing
Image credits: [1] Google, Digital Globe

11. Data preprocessing
Data downloaded from Open Street Map and Map Kibera:
•
•
•
•
•
Total area ~ 3000 Km2 (inc. Kibera)
6,557 points of interest
9,222 linear features (roads, waterways, railways etc.)
7,800 polygon features
582 water and sanitation features in Kibera:
• 158 public toilets
• 8 bio-centres
• Data loading into PostGIS using Python (GDAL/OGR, Fiona,
GeoAlchemy2)

12. Multi-criteria evaluation of transfer
station locations
• MCE analysis implemented using PostGIS
• Transfer station location parameters:
• Area ≥ 64m2
• Kibera boundary ≤ 50m
• Nearest road ≤ 5m

13. Image credits: [1] Map Kibera

14. Network Creation
• Spatio-topological model created using PostGIS
schema and NetworkX interface
• 19,558 edges (Nairobi and Kibera)
• 4,686,483 Km of road and footpath
• 16,347 nodes (junctions, toilets, transfer stations,
treatment plant)

15. Network Analysis
Total time for shortest network path:
• Each toilet to transfer station (158 trips)
• Accumulated waste, transfer station to treatment (7.9 trips)
• Vacutug capacity: 500 liters
• Large tanker capacity: 10,000 liters

16. Results

17. Image credits: [1] Map Kibera

18. Results
Image credits: [1] Google, Digital Globe

19. Conclusions
• Crowd-sourced map data enabling network analysis
• Spatio-topological network modelling within GIS
framework useful for sanitation planning
• Limited by data quality and availability
• Next steps,
• Attributing cost to networks
• Business case
• Tie to sanitation value chain
• Compare against pipe sewerage network
• Apply to other networks (solid waste etc.)

20. Dr Tomas Holderness
Geomatics Research Fellow
tomas@uow.edu.au
@iholderness