Vulnerability assessment using remote sensing: The earthquake prone megacity Istanbul, Turkey

Hazards like earthquakes are natural, disasters are not. Disasters result from the impact of a hazard on a vulnerable system or society at a specific location. The framework of vulnerability aims at a holistic concept taking physical, environmental, socio-economic and political components into account. This paper focuses on the capabilities of remote sensing to contribute up-to-date spatial information to the physical dimension of vulnerability for the complex urban system of the megacity Istanbul, Turkey. An urban land cover classification based on high resolution satellite data establishes the basis to analyse the spatial distribution of different types of buildings, the carrying capacity of the street network or the identification of open spaces. In addition, a DEM (Digital Elevation Model) enables a localization of potential landslide areas. A methodology to combine these attributes related to the physical dimension of vulnerability is presented. In this process an n-dimensional coordinate system plots the variables describing vulnerability against each other. This enables identification of the degree of vulnerability and the vulnerability-determining factors for a specific location. This assessment of vulnerability provides a broad spatial information basis for decision-makers to develop mitigation strategies

Geo Spatial Analysis for Tsunami Risk Mapping

Tsunami risk is a combination of the danger posed by tsunami hazard, the vulnerability of people to an event, and the probability of destructive tsunami. The spatial multicriteria approach made a possibility for integrating the vulnerability and risk parameters to assess the potential area that will be affected by the tsunami. The study applied the parameters of physical and social vulnerability and combined element at risk to assess tsunami risk in the coastal area of East Java Indonesia. All parameters in both tsunami vulnerability and tsunami risk assessment were analyzed through cell-based analysis in geographical information system. The weight of each parameter was calculated through the analytical hierarchy process. The results were provided as maps of tsunami vulnerability and tsunami risk. Tsunami risk map described five classes of risk. It described that coastal area with a low elevation and almost flat identified as high risk to the tsunami. The coastal area with a high density of vegetation (mangrove) was defined as the area with low level of tsunami risk. The existence of river and other water canals in coastal area was also analyzed for generating tsunami risk map. Risk map highlights the coastal areas with a strong need for tsunami mitigation plan

GIS-based seismic vulnerability assessment for the Istanbul Historical Peninsula

According to the Index of Risk Management-INFORM 2020 Report, Turkey was included in the group of “high-risk” countries in terms of humanitarian crises and disasters with an index score of 5.0 in 2019. In statistics related to the damage caused by disasters, it is known that natural disasters cause a 3% loss in Turkey's gross national product every year, and this rate approaches 4-5% with indirect losses. Since disasters cause socioeconomic, physical, and institutional losses, attention has been given to the importance of disaster management and risk reduction studies. This paper focuses on vulnerability assessments and presents a multi-criteria decision-making and earthquake-related vulnerability assessment method by using physical and socioeconomic parameters in the Historic Peninsula. A Multi-Criteria Decision Making (MCDM) method was applied in this study because vulnerability assessments are complex and depend on many different criteria. Due to its flexible structure, the Analytical Hierarchy Process (AHP), which is one of the MCDM methods widely used in urban vulnerability assessment studies, was preferred and integrated with Geographic Information Systems. As a result of the study, it is found that approximately 49% of the district is at a moderate vulnerability level in terms of socioeconomic characteristics. For the structural characteristics, this rate is found to be at a high vulnerability level of 93%. The remaining 7% is moderately vulnerable. In this context, emphasis should be placed on identifying risky structures and strengthening and renovating them in the Historic Peninsula. The results of the method proposed in this study can be used as a basis for risk reduction studies. In addition, it can be a guide in pre-disaster risk reduction studies and can be integrated into city planning processes to keep disaster damage at minimum levels and predict the damage that may occur in settlements. The proposed method is a low-cost and short-term analysis that can be used, especially in public institutions that lack a technologically qualified workforce

Multi-criteria decision making (MCDM) model for seismic vulnerability assessment (SVA) of urban residential buildings

© 2018 by the authors. Earthquakes are among the most catastrophic natural geo-hazards worldwide and endanger numerous lives annually. Therefore, it is vital to evaluate seismic vulnerability beforehand to decrease future fatalities. The aim of this research is to assess the seismic vulnerability of residential houses in an urban region on the basis of the Multi-Criteria Decision Making (MCDM) model, including the analytic hierarchy process (AHP) and geographical information system (GIS). Tabriz city located adjacent to the North Tabriz Fault (NTF) in North-West Iran was selected as a case study. The NTF is one of the major seismogenic faults in the north-western part of Iran. First, several parameters such as distance to fault, percent of slope, and geology layers were used to develop a geotechnical map. In addition, the structural construction materials, building materials, size of building blocks, quality of buildings and buildings-floors were used as key factors impacting on the building’s structural vulnerability in residential areas. Subsequently, the AHP technique was adopted to measure the priority ranking, criteria weight (layers), and alternatives (classes) of every criterion through pair-wise comparison at all levels. Lastly, the layers of geotechnical and spatial structures were superimposed to design the seismic vulnerability map of buildings in the residential area of Tabriz city. The results showed that South and Southeast areas of Tabriz city exhibit low to moderate vulnerability, while some regions of the north-eastern area are under severe vulnerability conditions. In conclusion, the suggested approach offers a practical and effective evaluation of Seismic Vulnerability Assessment (SVA) and provides valuable information that could assist urban planners during mitigation and preparatory phases of less examined areas in many other regions around the world

A GIS-based multi-criteria evaluation framework for uncertainty reduction in earthquake disaster management using granular computing

One of the most important steps in earthquake disaster management is the prediction of probable damages which is called earthquake vulnerability assessment. Earthquake vulnerability assessment is a multicriteria problem and a number of multi-criteria decision making models have been proposed for the problem. Two main sources of uncertainty including uncertainty associated with experts‘ point of views and the one associated with attribute values exist in the earthquake vulnerability assessment problem. If the uncertainty in these two sources is not handled properly the resulted seismic vulnerability map will be unreliable. The main objective of this research is to propose a reliable model for earthquake vulnerability assessment which is able to manage the uncertainty associated with the experts‘ opinions. Granular Computing (GrC) is able to extract a set of if-then rules with minimum incompatibility from an information table. An integration of Dempster-Shafer Theory (DST) and GrC is applied in the current research to minimize the entropy in experts‘ opinions. The accuracy of the model based on the integration of the DST and GrC is 83%, while the accuracy of the single-expert model is 62% which indicates the importance of uncertainty management in seismic vulnerability assessment problem. Due to limited accessibility to current data, only six criteria are used in this model. However, the model is able to take into account both qualitative and quantitative criteria

Multicriteria Fuzzy Analysis for a GIS-Based Management of Earthquake Scenarios

Objective of this article is the formulation andthe implementation of a decision-making model for theoptimal management of emergencies. It is based on theaccurate definition of possible scenarios resulting fromprediction and prevention strategies and explicitly takesinto account the subjectivity of the judgments of prefer-ence. To this end, a multicriteria decision model, basedon fuzzy logic, has been implemented in a user-friendlygeographical information system (GIS) platform so asto allow for the automation of choice processes betweenseveral alternatives for the spatial location of the investi-gated scenarios. In particular, we have analyzed the po-tentialities of the proposed approach in terms of seismicrisk reduction, simplifying the decision process leadingto the actions to be taken from directors and managers ofcoordination services. Due to the large number of vari-ables involved in the decision process, it has been pro-posed a particularly flexible and streamlined method inwhich the damage scenarios, based on the vulnerabilityof the territory, have represented the input data to de-rive a vector of weights to be assigned to different de-cision alternatives. As an application of the proposedapproach, the seismic damage scenario of a region of400 km2, hit by the 2009 earthquake in L’Aquila (Italy),has been analyzed

Assessment of Social Vulnerability to Floods in the Floodplain of Northern Italy

Practices for reducing the impacts of floods are becoming more and more advanced, centered on communities and reaching out to vulnerable populations. Vulnerable individuals are characterized by social and economic attributes and by societal dynamics rooted in each community. These indicators can magnify the negative impacts of disasters together with the capacity of each individual to cope with these events. The Social Vulnerability Index (SoVI) provides an empirical basis to compare social differences in various spatial scenarios and for specific environmental hazards. This research shows the application of the SoVI to the floodplain of northern Italy, based on the use of 15 census variables. The chosen study area is of particular interest for the high occurrence of flood events coupled with a high level of human activity, landscape transformations, and an elevated concentration of assets and people. The analysis identified a positive spatial autocorrelation across the floodplain that translates into the spatial detection of vulnerable groups, those that are likely to suffer the most from floods. In a second stage, the output of the index was superimposed on the flood hazard map of the study area to analyze the resulting risk. The Piemonte and Veneto regions contain the main areas prone to flood \u201csocial\u201d risk, highlighting the need for a cohesive management approach at all levels to recognize local capacities and increase communication, awareness, and preparedness to mitigate the undesirable effects of such events