ENDORSING PARTNERS

Spatial Network Modelling
for Sanitation Planning in
Informal Settlements

The following are confirmed...
Spatial Network Modelling
K
for Sanitation Planning in
Informal Settlements

Tomas Holderness1, Ruth Kennedy-Walker2, Davi...
The Sanitation Infrastructure Crisis
• Rapid city densification
• Peri-urbanisation growth
• Informal infrastructure

Imag...
The Sanitation Crisis

Image credits: [1] WHO/UNICEF
Critical Infrastructure?

A “frogman” manually
emptying a pit latrine in
Dar es Salaam

Image credits: [1] Florian Erzinge...
The Solution?

Vacutug:
• Vacuum pump truck
• 0.5m3 capacity
• 5 Km/h speed

Image credits: [1] Rémi Kaup; [2] Sustainable...
Transfer stations
• Reduce Vacutug travel
time
• Situated at the edge of
informal settlement
• Serviced by large
collectio...
A new approach
• Crowd-sourced mapping for spatio-toplogical network modelling
• Land cover, road/path network, amenity lo...
Methodology
Data preprocessing &
spatial database
construction

MCE site analysis

Create network

Network Analysis
Data preprocessing

Image credits: [1] Google, Digital Globe
Data preprocessing
Data downloaded from Open Street Map and Map Kibera:
•
•
•
•
•

Total area ~ 3000 Km2 (inc. Kibera)
6,5...
Multi-criteria evaluation of transfer
station locations
• MCE analysis implemented using PostGIS

• Transfer station locat...
Image credits: [1] Map Kibera
Network Creation
• Spatio-topological model created using PostGIS
schema and NetworkX interface
• 19,558 edges (Nairobi an...
Network Analysis

Total time for shortest network path:
• Each toilet to transfer station (158 trips)
• Accumulated waste,...
Results
Image credits: [1] Map Kibera
Results

Image credits: [1] Google, Digital Globe
Conclusions
• Crowd-sourced map data enabling network analysis
• Spatio-topological network modelling within GIS
framework...
Dr Tomas Holderness
Geomatics Research Fellow
tomas@uow.edu.au
@iholderness
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SMART International Symposium for Next Generation Infrastructure: Spatial Network Modelling for Sanitation Planning in Informal Settlements

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A presentation conducted by Dr Tomas Holderness SMART Infrastructure Facility, University of Wollongong. Presented on Thursday the 3rd of October 2013

Limited water and sanitation infrastructure in rapidly urbanising informal settlements can present significant health and environmental risks to populations in developing nations. Where formal pipe networks are not available,road-based sewage treatment-transportation options have been cited as a viable alternative. However, little research has been undertaken to evaluate the long term operational costs of such systems. In this paper we present an evaluation of network modelling, as a novel method to evaluate the costs of road-based sewage treatment transport options. Such analysis is made possible using crowdsourced, open geospatial data which allow us to examine costs based on different spatio-topological network configurations. It is envisaged that such a tool could be used by engineers as part of the sanitation planning process, to evaluate sanitation network implementation options. The paper includes a case-study based on the Kibera settlement in Kenya

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SMART International Symposium for Next Generation Infrastructure: Spatial Network Modelling for Sanitation Planning in Informal Settlements

  1. 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. 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. 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. 4. The Sanitation Crisis Image credits: [1] WHO/UNICEF
  5. 5. Critical Infrastructure? A “frogman” manually emptying a pit latrine in Dar es Salaam Image credits: [1] Florian Erzinger
  6. 6. The Solution? Vacutug: • Vacuum pump truck • 0.5m3 capacity • 5 Km/h speed Image credits: [1] Rémi Kaup; [2] Sustainable Sanitation Alliance
  7. 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. 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. 9. Methodology Data preprocessing & spatial database construction MCE site analysis Create network Network Analysis
  10. 10. Data preprocessing Image credits: [1] Google, Digital Globe
  11. 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. 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. 13. Image credits: [1] Map Kibera
  14. 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. 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. 16. Results
  17. 17. Image credits: [1] Map Kibera
  18. 18. Results Image credits: [1] Google, Digital Globe
  19. 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. 20. Dr Tomas Holderness Geomatics Research Fellow tomas@uow.edu.au @iholderness

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