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On the use of macro indicators to evaluate the sustainability of urban development

Abstract : Cities need to project themselves on the long-term to achieve sustainable planning choices. Scientific community can help through prospective models providing decision support. To be effective and easily discussed, models outputs can be summed up through simple and explicit indicators. These indicators make it easier to compare trajectories and to evaluate the relevance of the modeling hypothesis with stakeholders. Indeed, to collaborate with urban planners, quite unused to scientific modelling approaches in France, we understood that a clear visualisation and representation of the trajectories of the long-term evolution is necessary. Thus, we propose here an approach computing macro indicators to study urban sustainable development and assess a land allocation model. The methodology can be divided in three phases: a long-term land-use allocation model creating pathways for global evolution of urban main sectors, a spatially explicit dispatcher recreating the maps from the run and a post-processing tool computing the macro indicators. All steps are based on optimal tools but were separated because of deeply different logics. We apply this outline to Bordeaux Métropole, a French Southwestern metropolitan territory. The first prospective model is based on an optimal bottom-up paradigm. To fulfil a final demand of housing, mobility and jobs, the optimiser can invest in archetypes of various types: urban shapes, that use the land and allocate it to different uses (natural, residential or activity, roads, etc.), and buildings, that transform buildable land into housing, jobs and public equipments. These archetypes were previously characterized through statistical study of 2014 Bordeaux data (available publicly from national institutes). The optimisation is based on minimising the artificial land while answering the demand and the accent is therefore put on the densification. Whereas discussable as density is not so clearly and unequivocally linked with environmental efficiency, this choice was motivated by Bordeaux’s situation: the city is located near highly used agricultural lands (such as wine producers) and is already perceived as too mineral by its inhabitants. This model is then used to study a high demographic growth scenario where the population doubles in 2050 compared to 2014 instead of increasing by 35%. We project the results of the long-term model at a finer geographical scale through constrained maps and thereafter compute various indicators such as the temperature and the overall imperviousness. The computation of the macro indicators not available in the model is based on a prephase of data collection and modelling. We present here temperature case that can help study UHI phenomenon: we retrieved data from MeteoFrance results that we tried to link with global urban parameters (such as built density, impervious surface, natural area density, etc.) through bibliography study, statistical correlations and different machine-learning models. The goal here is to be able to evaluate the temperature by postprocessing the outputs of the main model and therefore compare the effects of the two scenarios on Bordeaux warming. The preliminary results on the first two steps show a strong densification of the different neighborhoods, result expected as presented above. The model makes a strong use of buildings elevation in certain regions.
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Contributor : Matthieu Denoux <>
Submitted on : Tuesday, November 24, 2020 - 11:10:41 AM
Last modification on : Thursday, December 3, 2020 - 3:11:07 AM


  • HAL Id : hal-03021197, version 1


Matthieu Denoux, Nadia Maïzi. On the use of macro indicators to evaluate the sustainability of urban development. The 26th International Sustainable Development Research Society Conference : Sustainability in Transforming Societies, ISDRS, Jul 2020, Budapest, Hungary. ⟨hal-03021197⟩



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