Fundamentos teóricos de la lectoescritura

Future cities have to be as sustainable as possible and the fundamental prerequisite to realise this condition is strictly related to their resilience characteristics. In other words, the link between sustainability and resilience relies on the quality of life levels of cities: if a city is resilient, it can recover from a disaster in an effective manner, reaching the previous level of quality of life, both in terms of happiness of inhabitants and environmental sustainability.

With this, by measuring the capability of urban systems to recover these properties, a rigorous framework, merging the engineering and ecosystems resilience approaches, can be developed in order to quantify the actual resilience of cities, and in particular, whenever they are subjected to extreme events.

The framework proposed by Bozza et al. (Bozza et al. 2015) is composed of 3 fundamental steps, as summarised in Figure 4.1:

1. global urban networks are defined by merging the social and physical networks in the un-damaged and damaged configurations. Efficiency, through robustness and redundancy measures, of these hybrid social-physical networks can be measured through well-established and rigorous complexity network theories. Such quantities represent a proxy of the capability of the city system to provide its citizens the services and the facilities they expect to receive.

2. quality of life and city performance indicators have to be identified to measure inhabitants’ happiness and environmental sustainability. 3. specific functions need to be calibrated to make such indicators dependent on the social-physical network metrics, identified in the previous step, also including social and economic background conditions. This step can be developed by means of well-established techniques in

decision-making and ecosystem theories (e.g. fuzzy logic, genetic algorithms, etc.).

Figure 4. 1 The proposed framework’s conceptual scheme (Bozza et al. 2015)

1.Given a configuration of the city, damaged or undamaged, we can compute the efficiency of the HSPN networks, by means of different rigorous indicators.

2. Citizens are “fed” by the physical systems.

Their happiness somehow “depends” on the rigorous indicators (efficiency, robustness, etc.) previously calculated.

We can establish a metrics for “happiness” and quality of life, that is city sustainability indicators.

3. We can find a system functions linking the “happiness” indicators to the network efficiency indicators. These functions will depend also on social-economic background

conditions.

By reiterating this process in different city configurations, during the recovery path and for different recovery paths, we can quantitatively manage resilience.

Particularly, hybrid social-physical networks (HSPNs) can be modelled as both topological and typological ones, being different through the methodology adopted for the quantification of resilience in the two cases. In order to better evaluate the effectiveness of the recovery process and to recognise the best strategies, scenario analysis can be performed and the framework can be reiterated for each scenario. Measurements, given by both engineering metrics and sustainability and quality of life indicators, have to be chosen in order to better describe social sustainability in the post-event phase.

As a result, the output of the proposed methodology is a set of indicators that can be evaluated for each considered strategy. As they are very synthetic measures of the efficiency of a recovery strategy, institutional authorities and local governments could use them to perform rapid choices soon after the occurrence of a catastrophe.

Present policies might be enhanced and best practices could be recognised, since when local authorities decide a recovery strategy will be implemented, they do not always know what the response of the urban environment will be. While the implementation of the suggested procedure allows for recognition of the strategies which best enhance resilience, sustainability and quality of life of a city are also applied by the performance of scenario analysis and a pre-event assessment of the city. According to Sperling et al. (Sperling F. and Szekely F. 2005), disaster managers have to overcome several barriers for an effective reconstruction. The main limitations are in the form of institutional barriers, efforts to access relevant information, lack of financial frameworks and limited financial resources, structural limit and the diversity of institutional structures all changing from one urban context to another. Moreover, disaster managers are also subjected to restrictions via regulatory compliance.

One of the major problems that a disaster manager has to face, given his human nature, is short-term thinking. This can easily lead to mistakes in

the case of a catastrophic event, when prompt decisions need to be made and when panic and chaos rule.

Obviously, it is not possible to solve all the problems that disaster managers usually have to face, but certain aspects may be enhanced, of course. Time and resources can be saved and scenario analysis might help to recognise the most efficient actions to adopt. For instance, whenever an earthquake occurs, it affects different adjacent urban contexts, or municipalities. Each municipality can be modelled in the post-event as a HSPN, both typological and topological, for known local damages. Hence, nodes and edges that are out-of-order are assumed to be unusable.

Once the actual damaged configuration is defined, a disaster manager can hypothesise different recovery strategies. They can be chosen as a set of the most resilient and sustainable strategies, already assessed with the scenario analysis previously performed for such municipalities. Simulations can be performed to evaluate resilience, efficiency, sustainability and quality of life indicators with a step-by-step procedure. Such measures are performed in the context of the typological approach as well the topological. As an output, the manager can acquire a set of indicators, where the values are varied according to the higher or lower resilience of the urban context. Therefore, the best strategy to be implemented can be chosen in a timely manner. The expected efficiency of such a methodology is stringently related to the time needed to use it. This is because of its straightforwardness, allowing managers to implement it as an automatic procedure given the simplicity of the instruments needed.

The disaster manager can also compare expected efficiency and resilience from each of the best strategies recognised for each municipality within the same urban context. This can be a further added value for the methodology, like in an example where two different best strategies are recognised for two adjacent municipalities and few differences are expected in the resulting resilience level. The manager can then choose to

implement the same strategy for both because of the opportunity to use the same means and resources. This would also result in saving economic resources, an important issue when dealing with post-catastrophe recovery.

4.2 DEFINING AND MEASURING HYBRID SOCIAL-PHYSICAL