Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
Despite a persistent call for a greater recognition of the underground in urban planning practices, cities still tend to address underground resources only when the need arises. Historically, this has proven costly for cities that have neglected the potential synergies and conflicts between, for instance, urban aquifers and underground infrastructure systems or building foundations. For urban planning to remain in a paradigm of needs to resources risks rendering conflicts between urban underground activities irreversible and possible synergies unattainable. Researchers and practitioners from multiple disciplines argue for the many benefits of underground development alternative renewable energy and drinking water sources, additional urban space and reusable geomaterials. Visualizing resource potential is a first step in raising awareness among planners of the capacities of the underground. Existing mapping methods tend to focus only on underground space development in contexts where the needs for the underground are already urgent and do not explicitly engage with the distribution of existing land uses. As an alternative to existing methods, this paper will present a procedure for mapping underground resource potential that incorporates four resources space, groundwater, geothermal energy and geomaterials developed by the Deep City project at the Swiss Federal Institute of Technology in Lausanne. San Antonio, Texas, a city with a complex relationship to an underground aquifer system but current little need and support for underground space, serves to illustrate the mapping method. Two future surface light rail and bus rapid transit lines, presented in recent planning reports, are examined in light of a latent but as yet untapped multi-resource underground potential. The paper concludes with a discussion of the applicability of the method to other cities and possible opportunities for improvement. (C) 2016 Elsevier Ltd. All rights reserved.
,