Assessing People´s Early Warning Response Capability to Inform Urban Planning Interventions to Reduce Vulnerability to Tsunamis : Case Study of Padang City, Indonesia

In the last decade, more emphasis is given on the human aspect of early warning or the attribute of “people-centered” early warning systems. This study seeks to better understand the specific conditions that shape people´s vulnerability in relation to their tsunami early warning response capability. The study lays emphasis on the bottlenecks within social conditions, issues of perception, and their linkages with urban evacuation spatial and infrastructure requirements. The study is based on an in-depth case study of the coastal city of Padang, Indonesia. Founded on literature study on vulnerability and early warning concepts, a conceptual study was developed. Here, vulnerability was defined as “the conditions which influence the level of exposure and capability of people to respond to the warning and conduct appropriate evacuation, and in the long term, to change those conditions and enhance their response capability”. The study is composed of three main assessment blocks: i) current spatial hotspots and bottlenecks within social conditions assessments; ii) assessment of perception issues related with on-going or planned interventions; and iii) assessment of urban planning´s role and influence on vulnerability and people´s response capability. The first assessment block consists of spatial and temporal distribution of various social groups in the exposed areas (dynamic exposure); their access to safe places; their access to warning; and their evacuation behaviour. The second assessment block examines various cognitive factors connected with objective knowledge as well as socio-psychological factors pertaining to vulnerability reduction. These are intention to evacuate (reactive action) and intention to support improvement of evacuation infrastructure and facilities (proactive action). Moreover, perceptions connected with challenges of possible relocation as well as overall tsunami preparedness are explored. The third assessment block explores the urban planning´s role and interventions linked with various response capability components. In order to assess different thematic areas, an interdisciplinary approach is required, using engineering and social behavioural sciences approaches. Therefore, the combination of qualitative and quantitative data collection and analysis methods is used. The results show that Padang´s current response capability varies according to its spatial and infrastructure setting as well as people´s socio-economic characteristics. Evacuation facilities and infrastructure were still lacking and their utilization was influenced by social conditions of the people. This implied a significant role for urban planning which needs to take into account various social groups´ specific needs while incorporating the importance of strategic risk communication within various interventions. The assessment needs to be integrated in the overall urban planning process and may provide guidance in finding the balance between long-term exposure reduction in dangerous areas and additional protection measures for mass evacuation

Risk Governance Deficits. An Analysis and Illustration of the Most Common Deficits in Risk Governance

IRGC defines risk governance deficits as deficiencies (where elements are lacking) or failures (where actions are not taken or prove unsuccessful) in risk governance structures and processes. They hinder a fair and efficient risk governance process. The deficits described by IRGC in this report have recurred over time and have affected risk governance in many types of private and public organisations, and for different types of risks. This report aims to help risk decision-makers in government and industry understand both the causes of deficits in risk governance processes and their capacity to aggravate the adverse impacts of a risk. With this understanding, it is hoped that risk practitioners will be able to identify and take steps to remedy significant deficits in the risk governance structures and processes

The Integration of Intergovernmental Coordination and Information Management in Response to Immediate Crises: Thailand Emergency Management

Recent occurrences of natural disasters and severe manmade hazards have increased awareness of the need for effective mitigation and response to extreme events. States of emergency require multiple agencies to perform multiple tasks simultaneously to return the situation to normal. This study proposes an inter-organizational model supported by the efficient use of information and communication technologies to assist multiple agencies in coordinating their actions more effectively during states of emergency. The model will assist participating agencies to develop the capacity to adapt to emergency conditions as well as the ability to replace other functions that fail in order to maintain the continuity of basic operations for the community until the state of emergency is cleared. Three recent cases of emergency operations in Thailand are examined to assess whether coordination among response agencies can be improved by using appropriately designed interagency operations. The complex environment of emergency response operations offers an extraordinary opportunity to investigate methods that may be used to understand and identify factors that build strength or lead to weakness in practice. The interdependence of sequential failures from sudden impacts such as the collapse of electrical transmission lines or a communication system provides a practical challenge for assessing the use of information and communication technologies in managing emergencies. Insights gained from this project may assist public agencies to work together more effectively.This research is conducted as an exploratory study with a nested case design. It employs both qualitative and quantitative methods of observation, interviews, social network analysis, document review and structured surveys to identify complementary characteristics rather than advocating a single style of research. Units of analysis are the emergency response organizations at national, provincial and local levels while units of observation are emergency response personnel in each organization. In addition, units of observation are stratified into top, middle, and operational levels of management in order to obtain information that may vary by levels of authority. Information obtained from multiple sources is analyzed to understand better the existing emergency response operations and how to improve the system effectively and efficiently.An alternative approach based on lessons learned from this study is to build systematic and adaptive collaboration among agencies, national, provincial and local levels, in emergency management of Thailand. The primary actors, Department of Disaster Prevention and Mitigation (DDPM), Bangkok Metropolitan Authority (BMA), Civil Emergency Relief Department (CERD), and District Offices (DO) can play effective roles in emergency response network under different scales of emergency. Insufficient information support and communication channels increase the difficulties of activating the action plan in wider response in states of emergency. Information technology and communication systems allow multiple agencies to share their knowledge and information they need in making informed decisions. Communication is a significant means to enable participating agencies to coordinate their operations simultaneously. These functions of information technology and communication help connect the entire emergency operation into a well-organized direction

Disaster and Pandemic Management Using Machine Learning: A Survey

This article provides a literature review of state-of-the-art machine learning (ML) algorithms for disaster and pandemic management. Most nations are concerned about disasters and pandemics, which, in general, are highly unlikely events. To date, various technologies, such as IoT, object sensing, UAV, 5G, and cellular networks, smartphone-based system, and satellite-based systems have been used for disaster and pandemic management. ML algorithms can handle multidimensional, large volumes of data that occur naturally in environments related to disaster and pandemic management and are particularly well suited for important related tasks, such as recognition and classification. ML algorithms are useful for predicting disasters and assisting in disaster management tasks, such as determining crowd evacuation routes, analyzing social media posts, and handling the post-disaster situation. ML algorithms also find great application in pandemic management scenarios, such as predicting pandemics, monitoring pandemic spread, disease diagnosis, etc. This article first presents a tutorial on ML algorithms. It then presents a detailed review of several ML algorithms and how we can combine these algorithms with other technologies to address disaster and pandemic management. It also discusses various challenges, open issues and, directions for future research

English for specific purposes

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