Assessment of Social Vulnerability Identification at Local Level around Merapi Volcano – A Self Organizing Map Approach

Abstract:

The application of Self-Organizing Map (SOM) to analyze social vulnerability to recognize the resilience within sites is a challenging tasks. The aim of this study is to propose a computational method to identify the sites according to their similarity and to determine the most relevant variables to characterize the social vulnerability in each cluster. For this purposes, SOM is considered as an effective platform for analysis of high dimensional data. By considering the cluster structure, the characteristic of social vulnerability of the sites identification can be fully understand. In this study, the social vulnerability variable is constructed from 17 variables, i.e. 12 independent variables which represent the socio-economic concepts and 5 dependent variables which represent the damage and losses due to Merapi eruption in 2010. These variables collectively represent the local situation of the study area, based on conducted fieldwork on September 2013. By using both independent and dependent variables, we can identify if the social vulnerability is reflected onto the actual situation, in this case, Merapi eruption 2010. However, social vulnerability analysis in the local communities consists of a number of variables that represent their socio-economic condition. Some of variables employed in this study might be more or less redundant. Therefore, SOM is used to reduce the redundant variable(s) by selecting the representative variables using the component planes and correlation coefficient between variables in order to find the effective sample size. Then, the selected dataset was effectively clustered according to their similarities. Finally, this approach can produce reliable estimates of clustering, recognize the most significant variables and could be useful for social vulnerability assessment, especially for the stakeholder as decision maker. This research was supported by a grant ‘Development of Advanced Volcanic Disaster Response System considering Potential Volcanic Risk around Korea’ [MPSS-NH-2015-81] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.

Keywords: Self-organizing map, Component Planes, Correlation coefficient, Cluster analysis, Sites identification, Social vulnerability, Merapi eruption 2010