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Spatial Indicators of Recovery after Earthquakes
Abstract
Several indices have been developed to measure vulnerability, but very few have been elaborated on the topic of recovery indices, and even fewer on the basis of spatial indicators. The objective of this research was to develop a methodology for monitoring and evaluating the recovery process of an area after an earthquake, beyond the physical aspect, based on spatial indicators. The development of this research entailed nine steps: 1) Selection of a case study area, 2) literature review 3) fieldwork, 4) selection of a sampling area in the city, 5) analysis of index of site preference among the relocated communities in the new settlements, 6) monitoring changes in buildings, 7) selection of the variables and indicators of recovery 8) integration of the spatial indicators in a recovery index; and 9) measuring recovery: hotspots. The case study area of the research is the Italian city of L’Aquila, which was struck by an earthquake on April 6th 2009. Fourteen categories of building conditions were identified: new buildings, construction on-going, partially enabled, reconstructed, reconstruction on-going, earthworks, reconstruction projected, repaired, debris removed, propped, inhabited, damaged, restricted use and demolished. Thirteen categories of building use were recognized: residential, commercial, transport, amenity, religious, hospitals, office, educational, industrial and sports facilities, hotels, monuments and not inhabited. Both indicators: namely the building condition and building use were aggregated into a recovery index in terms of the physical and socio-economic dimensions respectively. Residential buildings, reconstructed buildings, new buildings, transport, and commercial facilities were considered to be the most important variables for the recovery progress of a city. The statistical analysis revealed that the preference to search for another site was significantly correlated with the distance between new settlements and the city center of L’Aquila. To an even higher degree it was correlated with the travel time. The results demonstrated a negative relationship, in which the preference to search for another housing site decreased with an increase in the number of urban facilities in the settlement. There was no correlation between the number of inhabitants per settlement and the number of urban facilities. The regression indicated that the distance and the travel time between the new settlements and the inner city and the lack of urban facilities strongly influences the preference to either stay or to move. Although the percentage of damaged and propped buildings is still high in the city center of L’Aquila by 2014, buildings are already reconstructed and the percentage of buildings with on-going reconstruction and reconstruction projected has soared, while the percentage of buildings in restricted use declined sharply in the last two years. The percentage of buildings for residential use, commercial, office and religious facilities, as well as hotels has steadily increasing in the last five years (2009-2014). The lack of resilience in L’Aquila is demonstrated by the failure to return five years later to at least the original situation before the earthquake. It is unlikely that L’Aquila can be considered a resilient city, where the reconstruction of the most affected areas of the city is still ongoing and where people express dissatisfaction with respect to the place where they were relocated, because of the distance and the travel time to the inner city, and the lack of facilities in the place, where they were relocated. The reconstruction process in the city centre of L'Aquila seemed to stagnate. Nevertheless, I can conclude that the recovery process in L’Aquila has not come to a halt, its progress was very slow in the past, but has now accelerated, and can finally be evaluated again in 2019.
... The literature review identified 146 indicators of recovery following earthquakes, of which 42 (29%) were classified as physical indicators, 42 (29%) as social indicators, 30 (21%) as economic indicators, 21 (14%) as institutional indicators, 5 (3%) as cultural indicators, and 6 (4%) as ecological indicators (Contreras, 2015). The summarized version of the indicators selected to define the post disaster recovery phase achieved by L'Aquila in 2014 (five years after the earthquake) are listed in The highest score (6 points) was obtained for the early recovery phase, followed by the recovery phase (4 points), the development phase (2 points) and the relief phase (1 point). ...
... The relocation of most of the people left homeless by the earthquake is not proof of recovery. The communities in the new settlements, which are located far from the center of expressed dissatisfaction with the state of affairs and a desire to move to another location because of the distance and travel time to the center of L'Aquila (Contreras et al., 2013), the lack of employment possibilities, and the general lack of facilities (Contreras, 2015). This situation is encouraging migration away from the area (Ambrosetti & Petrillo, 2016) because a large proportion of the economic activities in L'Aquila take place in the central business district, which has been referred to by Arens (2014) as the biggest construction site in Europe. ...
A number of indices have been developed for measuring vulnerability to disasters, but little attention has been paid to recovery indices particularly with respect to earthquakes. Post-disaster periods are usually divided into four phases based on specific time intervals following an event, which have been assigned a variety of different names. The name established by the UNDP ("relief", "early recovery", "recovery" and "development") have been used in this paper. This research examines the hypothesis that the post-disaster recovery phases in an affected area should be defined by the progress achieved in the recovery process, rather than simply by the amount of time elapsed since the event. The methodology employed involved four steps: (1) literature review, (2) fieldwork (3) the selection of indicators, and (4) assessment. The case study area was L’Aquila in Italy, which was struck by an earthquake in 2009. Each phase of the recovery progress at L'Aquila was assigned a score according to the progress achieved, with the highest score going to the early recovery phase, followed by far lower scores for the development phase and the recovery phase, with the relief phase (having already been completed) failing to score any points. The results have demonstrated the possibility of determining post-disaster recovery phases according to activities and other variables or indicators, rather than simply according to periods of time. It is, however, recommended that assessments of the stage that has been attained in the recovery process be made at specific times in the post-disaster period, such as after one, three, five and ten years.
... In this case, recovery was focused on three dimensions: urban, economic and lifestyle (Karatani & Hayashi (2007). This process is considered the basis of post-disaster recovery process research, as it resulted in the creation of recovery indicators and models (Karatani et al., 2004;Karatani & Hayashi, 2007;Contreras, 2015Contreras, y 2016. By contrast, the reconstruction policy after the 2010 earthquake and tsunami in Chile has been intentionally focused on physical aspects such as construction of new houses and inefficient hard mitigation measures rather than restoration of living conditions. ...
Tsunamis are among the most significant hazards in coastal settlements. Mitigation measures have been focused mainly on physical aspects, and few studies have addressed vulnerability and resilience in a multidimensional approach. The main objective of the present work is to assess changes in vulnerability and, consequently, risk, considering a time-space dimension. Three deterministic tsunami scenarios based on historical events were analyzed, and vulnerability analysis with an emphasis on social cohesion and community organization in pre-reconstruction (2012) and post-reconstruction (2017) conditions was carried out using physical, socioeconomic and social organization variables. The extreme scenario was found to be a 2010-like tsunami, and high levels of social trust and community cooperation were found in pre-reconstruction conditions, which decreased in post-reconstruction conditions due to the relocation of the affected population to other parts of the region. Therefore, it can be concluded that even though physical aspects are important for improving the livability of an affected place and the quality of life of its inhabitants, intentionally biased reconstruction processes (focused mainly on physical aspects) do not effectively reduce risk. Finally, it is crucial to include social capital and social resilience in public policies to implement more comprehensive and successful reconstruction processes.
... The percentage of buildings demolished reached 3 % (24) in 2014 from just over 1 % (8) in 2012, but this number decreased again to 2 % (18) in 2016. The percentage of damaged buildings remained high at 32 % (239) of the sampling buildings in the city center of L'Aquila in 2014(Contreras 2015) and slightly decreased to 28 % (214) in 2016. These numbers were the reason to assign the value of ''1'' to the change in building condition indicator for the early recovery and recovery phases.Using the same sampling area and sampling size (753 buildings) to monitor the building condition change from 2010 to 2016, it was found that the percentage of uninhabited buildings in the former restricted zone has been slightly decreasing since 2010, when 86 % (648) of the buildings included in this sampling were not inhabited. ...
A number of indices have been developed for measuring vulnerability to disasters, but little attention has been paid to recovery indices. Post-disaster periods are usually divided into four phases. The terms established by the United Nations Development Programme for post-disaster phases—relief, early recovery, recovery, and development—are used in this article. This research examines the hypothesis that the boundaries between post-disaster recovery phases are fuzzy and should be defined by the progress achieved in the recovery process, rather than by the amount of time elapsed since the event. The methodology employed involved four steps: fieldwork, mapping, identification of indicators, and assessment. The case study area was the city of L’Aquila in the Abruzzo region of central Italy, which was struck by an earthquake in April 2009. For each phase of the recovery process in L’Aquila a score was calculated based on the progress observed in 2016, 7 years after the earthquake. The highest score went to the early recovery phase (14 points), followed by the recovery phase (13 points), the development phase (12 points), and the relief phase (4 points). The results demonstrate the possibility of defining post-disaster recovery phases in an affected area based on measuring achievements through indicators rather than defining recovery phases in terms of elapsed time after a disaster.
After the earthquake in 2009, L’Aquila (Italy) began a recovery process characterized by a delay in the reconstruction of the city center. Between 2010 and 2014 a recovery index was formulated based on spatial indicators, such as building condition and building use, to measure the progress of the recovery process in L’Aquila. Eight years after the earthquake, the work presented in this paper was used to update the recovery index, not only by measuring the progress of the recovery in L’Aquila but also by validating the usefulness of the proposed recovery index. To achieve this objective, the current research considered the same set of spatial indicators that were used to determine the progress of the recovery in L’Aquila by 2010, 2012, and 2014 in the revaluation of the expert criteria. It was found that in 2016 the number of reconstructed buildings and buildings under ongoing construction had significantly increased and the number of buildings with residential and commercial use had increased along the main roads. While progress was observed in the overall building condition, there was no significant progress in the building use. This poses several questions about how the recovery process can contribute to the return of the inhabitants to the city center of L’Aquila. The paper concludes that the proposed recovery index is useful for identifying the spatial pattern of the recovery process in an urban area affected by an earthquake. At the same time, this recovery index allows the recovery progress to be quantified based on indicators.
Our research is based on analyses of broad literature, collection of original material through fieldwork, and personal experience in L’Aquila, an Italian city heavily da- maged by an earthquake in 2009. We took this site as a context of induced scarcity and of some Grassroots Urban Initiatives developed within it. After giving a broad narrative of the earthquake and institutional emergency management, we will con- centrate on two Grassroots Urban Initiatives: the “Assemblea cittadina dell’Aquila” (City Assembly of L’Aquila) and the “Comitato per la Rinascita di Pescomaggiore” (Board for the Rebirth of Pescomaggiore). For each initiative analysed, we decided to take into account why and in which context they developed, who is involved, what their objectives are and finally the main similarity with Social Ecology.
The lack of coordination between government agencies, involvement of the collaboration networks existing in the community, and incorporation of spatial planning in the location of the new settlements around L'Aquila (Italy) after the 2009 earthquake has delayed reconstruction of the city centre. The displaced population was relocated to 19 new settlements. These new settlements are characterized by a lack of urban facilities. The aim of this paper was to analyze the relationship between urban facilities, collaboration networks and lack of spatial resilience in the recovery process in L'Aquila. Specifically, we focused on the preferences of inhabitants to search for alternative housing sites to the settlements they were originally relocated to, as a proxy for dissatisfaction in the new settlements around L'Aquila. Our approach consisted of three steps: 1) fieldwork, 2) survey and 3) correlation/regression analysis. The results demonstrated a strong relationship where preference to search for another housing site decreases with increasing number of urban facilities in the settlement and increases with travel distance to the urban core of L'Aquila. We can conclude that the allocation of facilities was oriented to supply basic services, but neglected other needs of the community during the recovery process, which reduces its resilience.
A number of indices have been developed for measuring vulnerability to disasters, but little attention has been paid to recovery indices. Post-disaster periods are usually divided into four phases. The terms established by the United Nations Development Programme for post-disaster phases—relief, early recovery, recovery, and development—are used in this article. This research examines the hypothesis that the boundaries between post-disaster recovery phases are fuzzy and should be defined by the progress achieved in the recovery process, rather than by the amount of time elapsed since the event. The methodology employed involved four steps: fieldwork, mapping, identification of indicators, and assessment. The case study area was the city of L’Aquila in the Abruzzo region of central Italy, which was struck by an earthquake in April 2009. For each phase of the recovery process in L’Aquila a score was calculated based on the progress observed in 2016, 7 years after the earthquake. The highest score went to the early recovery phase (14 points), followed by the recovery phase (13 points), the development phase (12 points), and the relief phase (4 points). The results demonstrate the possibility of defining post-disaster recovery phases in an affected area based on measuring achievements through indicators rather than defining recovery phases in terms of elapsed time after a disaster.
After the earthquake in 2009, L'Aquila (Italy) started a torturous recovery process, characterized by a delay in the reconstruction of the city center, the political and legal intrigues, and the dissatisfaction of the population with the decisions made and actions taken by the government. Between 2010 and 2014 we formulated a recovery index based on spatial indicators, such as building condition and building use, to measure the progress of the recovery process in L'Aquila. Now, seven years after the earthquake, we are not only interested in measuring the progress of the recovery in L'Aquila, but also in validating the usefulness of the proposed recovery index. To achieve this objective, we are going to consider the same set of spatial indicators and expert criteria that we considered to determine the progress of the recovery in L'Aquila by 2010, 2012, and 2014. Over these years, the city center of L'Aquila was selected as the sampling area, to establish the progress of the recovery in the whole city. In 2016 we found that the number of reconstructed buildings and buildings under ongoing construction has significantly increased, followed by the number of inhabited buildings. The number of buildings classified as partially enabled, propped, reconstruction projected, and damaged had greatly decreased by 2016, while the number of demolished buildings and buildings with restricted use slightly increased. The number of buildings with residential and commercial use increased along the main roads by 2016. Paradoxically, while progress was observed in the overall building condition, there was no significant progress in the building use. This poses several questions about the dynamics of the returning process of the former habitants of the city center in L'Aquila. We can conclude that the proposed recovery index is useful for identifying the spatial pattern of the recovery process in an urban area affected by an earthquake. At the same time, this recovery index allows us to quantify the recovery progress based on indicators.
On September 19, 1985, at 7:14 a.m. an earthquake reaching a magnitude of 8.1 on the Richter scale and lasting almost two full minutes hit the coast of Mexico, rocking its capital city and shaking its buildings and its people. The next day, at 7:38 p.m., Mexico City experienced a second tremor of an almost equal magnitude on the Richter scale, 7.5. What has come to be known as the Mexico City earthquake, then, was in actuality two earthquakes, although those who experienced it lived through a single disaster whose longer-term reverberations were as powerful as the first set of tremors that hit the city on that initial day in September. The earthquake, or those two days of tremors big and small, produced a physical disaster on a scale not seen since the destruction of the city in 1521, when Hernán Cortés’s forces defeated the ancient Aztec city of Tenochtitlan. This same battle site later served as the seat of eighteenth- and nineteenth-century Spanish colonial power and subsequently marked the place where the majority of the 1985 earthquake damage occurred. After the first day alone, 250 buildings were completely destroyed with 50 more at risk of collapsing; thousands of others were damaged or considered to be unusable. Five thousand people were injured with more than 1,000 still trapped under the debris; more than 250,000 people were homeless. The city lacked telephone and electricity services. After the second day’s quake, when more reliable statistics began flowing in, 2,000 were officially confirmed dead (although close to 7,000 cadavers had been identified) with 28,000 still listed as missing; more than 7,000 victims were being treated at relief stations, with 30,000 at gyms and other sites turned into shelters. More than 800,000 residents were ultimately forced to abandon their homes and sleep in the open air. Official statements later acknowledged 5,000 killed and 14,000 injured; but an independent final tally accounted for 2 million residents temporarily made homeless and thousands dead, tens of thousands injured, 100,000 damaged building units (mostly residential), and hundreds of thousands of residents made permanently homeless.
Spatial information has traditionally helped specialists providing advice on programs and project orientation in natural resource management. Remote sensing and Geographic Information Systems (GIS), as the basis of a Resource Information and Management System (RIMS), constitute powerful tools for generating data that will improve the understanding of various natural-resource-related problems. The RIMS demonstration project conducted at the Chiang Mai Valley test site focused on application in forest management, land-use evaluation for agricultural purposes and erosion susceptibility assessment. -from Authors
