Mapping urban underground potential in Dakar, Senegal: From the analytic hierarchy process to self-organizing maps

Underground Space

Michael R. Doyle¹ 

[1] Deep City Project, Laboratory for Environmental and Urban Economics (LEURE), École polytechnique fédérale de Lausanne (EPFL), Switzerland;

关键词: Urban planning;    Geographical information systems;    Geomaterials;    Groundwater;    Geothermal;    Underground space;   

DOI  :  

来源: DOAJ

【 摘 要 】

This article presents a mapping method that seeks to provide urban planning with a diagnostic overview of the underground resources of an urban area. Resource potentials (for buildable space, groundwater or geomaterial extraction and geothermal energy) tend to be investigated on a needs-only basis once a project or plan has already been elaborated. This paradigm of ‘needs to resources’ risks favoring single-use rather than multi-use underground development, leading to unforeseen conflicts between possible uses (e.g., pollution of an aquifer or congestion of infrastructure) or the irreversible loss of potential synergies (e.g., geothermal collectors on building foundations). The Deep City project at the EPFL in Switzerland has been working on an alternative paradigm of ‘resources to needs’, which is a holistic approach addressing the underground as a source of opportunity in synergy with surface development for curtailing urban sprawl while preserving public places or parks. The method, which combines geological and surface urban data, produces maps of individual and combined resource potentials without prioritizing any particular planning objective. This communication will present the method and the resulting maps through a case study conducted in 2016 in the city of Dakar, Senegal. After first summarizing the Deep City project and the mapping method, the urban and geological conditions of Dakar will be presented, followed by the application and results of the Deep City method. The calculation of the combined potentials map is an opportunity to compare two alternative methods of combination, the Analytic Hierarchy Process and Self-Organizing Maps (SOMs). Although the mapping method does not require complicated data collection or analysis, the SOM may be better suited both for dealing with larger quantities of data and for providing more meaningful mappings of geological and urban data in three dimensions.

【 授权许可】

Unknown