Mapping Vulnerable Earthquake Disaster Class-I Cities for Disaster Risk-Reduction and Community Resilience in India

2018 ◽  
pp. 75-93
Author(s):  
Bupinder Zutshi ◽  
Homolata Borah ◽  
Priya Bhakat
2020 ◽  
Vol 156 ◽  
pp. 01011
Author(s):  
Osmar Shalih ◽  
Hafid Setiadi ◽  
Triarko Nurlambang ◽  
Widyawati Sumadio

Along with the increase in large and medium-scale disasters in the world, including in Indonesia, in the last decade, many theories and practices have developed in terms of measuring and improving disaster resilience. This study discusses the conceptual model of community-level disaster resilience and disaster risk reduction. Using a basic conceptual model for spatial protection to geological hazard, research examines the role of community resilience in reducing risk by using social dimensions. To explore the conceptual model of spatial resilience at the community scale, case studies conducted in two disaster events, are (1) communities affected by landslides in Cisolok, Sukabumi District on 31 December, 2018 and (2) Sunda Strait tsunami in Pandeglang tourism area on 22 December, 2018. Research suggests that the importance of social capital in terms of forming community resilience is related to disaster risk reduction. Social network, social experience, social knowledge and belief systems, contribute to increasing resilience and disaster risk reduction. The results of this study are the importance of building social capital and spatial resilience of communities in reducing disaster risk.


2021 ◽  
Vol 331 ◽  
pp. 04012
Author(s):  
Putranesia Thaha ◽  
Febrin Anas Ismail

This research begins by comprehensively exploring previous research related to community resilience and what steps are used to increase community resilience in reducing disaster risk. Conceptually, it is known that the fatigue model accumulated by the time system, infrastructure system, governance system, regulatory system, and hazard system for disaster risk reduction is often associated with weakening community resilience. It is often associated with catastrophic events, which are sometimes predictable and unpredictable. In manual decision-making, people are aware of the inconsistency of subjective decisions. A decision support system hypothesizes that it will take less time to explore data to make faster and more informed decisions. As a result of this concept, it is possible to reduce the number of wrong choices when dealing with disaster risk reduction issues. In terms of disaster risk reduction, the power of decision support systems is discussed in this paper to find a framework for its effectiveness as relative decision making will differ on different dimensions of Resilience.


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