Urban vulnerability (UV) in general, and its adaptive component in particular, have become key issues for a sustainable urban development [1
] which have lead, in recent decades, to the improvement of the existing urban vulnerability assessment models (UVAMs). In the pursuit of this, several requirements have been pointed out, all of which should be simultaneously addressed by vulnerability assessment methods in order to integrate vulnerability assessment into current urban strategic planning (USP) [2
] and fill the gap between assessment and actions [6
]. Specifically, the advancement in multi-scale assessment methods is needed to afford a multi-scale assessment framework providing an integrated evaluation of entities at the three relevant levels of government (Central government, regions, and cities), with which to avoid resources allocation problems [7
Dor and Kissinger [9
], as well, pointed out the importance and need of analysing the potential contribution of measures to urban sustainability at the top and down scales of a system, while Rega et al. [10
] remarked the relevance of the political–administrative context (region, province, cities) when assessing a territory’s urban sustainability. This work contributes the need of having into account the governmental structure when developing comprehensive assessment models by demonstrating the influence of entities’ governmental context risk-level over entities’ risk of increasing vulnerability (e.g., the influence of a region’s risk over its provinces’ risk and so on). Following this idea, the presented methodology provides the holistic and multi-scale quantitative assessment required for achieving urban sustainability [9
] and demanded by Strategic Environmental Assessment [10
]. While other methodologies have undertaken the evaluation of resilience at buildings, parcels, neighbourhoods and communities scales [4
], this study investigates the effect of entities’ political–administrative context’s risk over entities’ risk at the municipal, provincial and regional scales of urban vulnerability. This multi-scale assessment meets the requirements for being integrated into strategic planning to produce a comprehensive plan of actions, to be implemented at local (down) scale, contributing to ameliorate vulnerability at national (top) scales [8
This paper presents a Decision Support System (DSS) implementing a methodology previously developed [11
] to provide an urban vulnerability assessment of Spain at regional, provincial, and city scales that can be integrated into strategic planning tools for ameliorating this problem [8
]. The DSS is a Multi Objective Optimization (MOO) decision-making tool [12
] for simultaneously addressing all the requirements pointed out for vulnerability assessment, as well as for searching the set of indicators best representing urban vulnerability accordingly to several objectives. These objectives were closeness to expert judgment, maximise goodness of fit of the statistical model representing vulnerability’s evolution over time, and the robustness of each set of indicators against data uncertainty [11
]. As a result, the method rendered several sets of indicators among which the decision-makers had to choose.
This selection, on the other hand, may be hindered by a dimensional problem with the number of available alternatives rendered by the process.
Zio and Bazzo [13
] pointed out that only a manageable number of alternatives, representing the Paretofront, should be offered for selection to the DMs. However, MOO processes typically yield a large amount of solutions [14
], seeming a cloud of solutions rather than a manageable set of them. This particularity more patently affects many-objective configurations [15
], especially in the presence of conflicting or not aligned objectives, as in the case of selectin urban UVAMs. The large amount of solutions, also called the “curse of dimensionality” by Kukkonen and Lampinen [16
] (Figure 1
, Step 1), requires a specific treatment enabling DMs to focus their attention on those alternatives found relevant [11
]. The employment of data analytics, such as cluster analysis [13
], or visual analytics, such as “brushing” solutions [19
], have previously been used for alleviating the problem of unmanageable sets of alternatives. However, there is a lack of such approaches to reduce the dimension of solutions provided by UVAM selection decision frameworks.
The presented decision support system addresses this problem by extensive usage of visual analytics all along the decision process with the aim of selecting a proper UVAM (Figure 1
, Step 3) for the assessment of UV in Spanish regions, provinces, and cities larger than 100,000 people, capitals of provinces, and all municipalities in the province of Valencia. On one hand, visual analytics (Figure 1
) allow focusing the analysis into a limited decision space, interactively bounded by the analyst. On the other hand, the decisional tool presented enables DMs to synthesise, by means of cluster analysis (Figure 1
, Step 2), the space of solutions into a manageable number of representative ones, facilitating the process of analysing alternatives and selecting the proper one. Visual analytics allow for an ex post, dynamic selection of the criteria employed to choose the representative solutions of each cluster, as well as the number of clusters desired by the analyst, improving the extraction of knowledge. The whole DSS is implemented as a software, which we have denominated VisualUVAM, in order to provide the decision-makers with the necessary guidance along the whole process, allow the necessary interactions between the decision-makers and the process, and enable them to interactively set up both the bounds required to limit the space of solutions, as well as the necessary parameters for synthesizing them.
Thus, the novelty of the presented DSS relies, on one hand, in the innovative combination of clustering methods and visual analytics to solve the “curse of dimensionality” problem in the selection of UVAM, contributing to alleviating burdens on the decision-making task. On the other hand, the presented method affords for the first time a comprehensive and multi-scale assessment, from national to municipal scales, of urban vulnerability throughout a territory. Based on the results yielded by this methodology, this work has been the first in identifying, on a quantitative footing, the effect of the context’s risk of vulnerability over an entity’s risk, which underpins the idea of vulnerability’s propagation across scales pointed out by Adger [21
The remainder of this paper is organised as follows. In the methods section, both the decision-making framework and the assessment model are presented, along with a description of the information collection process. Then, two tools, designed accordingly to this methodology, are presented in the following section. The first one gathers and transforms the qualitative information required by the second, which articulates the decisional model for selecting UVAMs. Along with this section, the implementation of these tools on Spain, as well as the results produced by their operation, are portrayed to the reader. Finally, conclusions are drawn in the final section.
6. Conclusions and Further Research
Throughout this research, a method for selecting urban vulnerability assessment models has been developed to obtain a tool that allows for the generation of results according to the latest trends in the field of urban strategic planning. The whole process was implemented in VisualUVAM, a software that integrates quantitative and qualitative information to find out relevant multi-scale assessment alternatives that satisfy the multiple criteria demanded for urban vulnerability assessment models. This process, however, yields a large number of pareto-optimal alternatives among which to decide, a problem for the decision-maker also known as the “curse of dimensionality”. VisualUVAM addresses this problem by means of cluster analysis and visual analytics. Through an ex post selection of both the number of clusters and of the criterion used to choose the solution representative of each cluster, the proposed method synthesises the original set of alternatives into a manageable number of options, therefore alleviating the decisional burden entailed by a large set of alternatives.
On the other hand, the proposed formulation of the urban vulnerability phenomenon considers its dynamic aspects over both time and the administrative structures in which it develops, offering a consistent and comprehensive assessment along the scales of municipality, province and region, and allows contextualising entities in terms of the risk of their correspondent entity at the upper scale (e.g., risk of the province to which a city belongs). Our work has demonstrated how high-risk level contexts contribute to increase the risk of vulnerability of the entities affected, underpinning the idea of vulnerability’s propagation across scales, and pointing out the need of incorporating these relations by means of a multi-scale assessment of this phenomena. This approach also enables the design of comprehensive plans, implemented at city scale, for addressing urban vulnerability at national, regional, and provincial scales. Further, the results allow for analysing entities not only as a function of their own characteristics, but also to contextualize them with regard to their governmental context, which would be of help in understanding to which extent entities would be affected by their political-administrative environment.
In addition, this work presents a software that facilitates the collection of expert preferences, allowing them to check the consistency of their judgments in real time, review them before its submission, and therefore improve the quality of this analysis. For the experts consulted, the most relevant indicators in order of priority are the population density (inhabitants per hectare), the density of housing (Viv/Ha), the percentage of elderly people aged 75 and over (%), and the percentage of unipersonal households over 64 years of age (%). At the level of aspects, the most important are the social structure and dwellings size. These results contrast strongly with the criterion used in the analysis of the Spanish Observatory of Urban Vulnerability, based on only three indicators, considering them equally important.
Despite the importance of the contributions indicated, the method developed during this research still contains limitations. The assessment framework employed is based on that of the Observatory of Urban Vulnerability, which proposes a basic classification of vulnerable or non-vulnerable entities based on the exceeding of a reference value in any of the basic indicators. However, the results of this research force us to question the suitability of the selected indicators. Therefore, it is necessary to deepen the study of the most appropriate set of basic indicators.