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dc.contributor.author | Salas, J. | es_ES |
dc.contributor.author | Yepes, V. | es_ES |
dc.date.accessioned | 2020-02-26T21:00:39Z | |
dc.date.available | 2020-02-26T21:00:39Z | |
dc.date.issued | 2019 | es_ES |
dc.identifier.issn | 0959-6526 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/137883 | |
dc.description.abstract | [EN] There is a growing interest in model-based decision support systems contributing to strategic planning. The application of these in the case of urban infrastructure planning requires methods specifically aimed at addressing the relational uncertainties arising from the complex, multi-scale, nature of this field. This study presents UPSS, a comprehensive urban planning support system integrating the generation of planning alternatives, the evaluation of alternatives under a set of relevant scenarios selected dynamically in a cognitive way, and the proposal of policies to accompany the planning alternative. For this purpose, UPSS integrates two novel methods. These deal respectively with the ex post identification of relevant scenarios for the evaluation of the vulnerability and resilience of the alternatives, and with the assessment of relational uncertainty. According to the risks and opportunities borne by the system, the process makes it possible to select an infrastructure plan to alleviate the problem of urban vulnerability, as well as a set of relational contracts for its proper implementation across the different governmental scales of the infrastructure system. The whole process is tested via a case study, in which USPP first proposes optimal urban infrastructure plans that contribute to ameliorate the problem of urban vulnerability in Spain, then evaluates the risks and opportunities attached to the planning alternatives, and finally presents sets of policy measures to accompany the implementation of the alternative selected. | es_ES |
dc.description.sponsorship | The authors acknowledge the financial support of the Spanish Ministry of Economy and Competitiveness, along with FEDER funding (Project: BIA2017-85098-R). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Journal of Cleaner Production | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Urban vulnerability | es_ES |
dc.subject | Infrastructure planning: Multi-scaleRisk | es_ES |
dc.subject | Opportunity | es_ES |
dc.subject | Relational uncertainty | es_ES |
dc.subject.classification | INGENIERIA DE LA CONSTRUCCION | es_ES |
dc.title | MS-ReRO and D-ROSE methods: Assessing relational uncertainty and evaluating scenarios risks and opportunities on multi-scale infrastructure systems | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.jclepro.2018.12.083 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/BIA2017-85098-R/ES/DISEÑO Y MANTENIMIENTO OPTIMO ROBUSTO Y BASADO EN FIABILIDAD DE PUENTES E INFRAESTRUCTURAS VIARIAS DE ALTA EFICIENCIA SOCIAL Y MEDIOAMBIENTAL BAJO PRESUPUESTOS RESTRICTIVOS/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería de la Construcción y de Proyectos de Ingeniería Civil - Departament d'Enginyeria de la Construcció i de Projectes d'Enginyeria Civil | es_ES |
dc.description.bibliographicCitation | Salas, J.; Yepes, V. (2019). MS-ReRO and D-ROSE methods: Assessing relational uncertainty and evaluating scenarios risks and opportunities on multi-scale infrastructure systems. Journal of Cleaner Production. 216:607-623. https://doi.org/10.1016/j.jclepro.2018.12.083 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.jclepro.2018.12.083 | es_ES |
dc.description.upvformatpinicio | 607 | es_ES |
dc.description.upvformatpfin | 623 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 216 | es_ES |
dc.relation.pasarela | S\374258 | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |