An Integrated GIS and Big Data Platform for Meteorological Disaster Risk Management and its Application

2020 ◽  
Author(s):  
Ying Li
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Disaster Risk Reduction ◽  
Disaster Risk ◽  
Professional Services ◽  
Decision Makers ◽  
Meteorological Disaster ◽  
Data Application ◽  
Big Data Application ◽  
Meteorological Disasters

<p><span>Under the background of global changes, the frequency and intensity of various meteorological disasters are increasing, which poses a great challenge to the risk management worldwide. The Sendai Framework was put forward by the third world conference on disaster reduction, providing a roadmap for the international community to respond to disaster risks. In recent years, China has stepped up its implementation of disaster risk reduction actions, but there has been no systematic platform to supply professional services of meteorological disaster risk reduction for decision makers. In order to effectively reduce the risk of meteorological disasters and meet the urgent need in service, Beijing Climate Center of China developed a Meteorological disaster risk management platform (MDRMP), which integrates the technology of big data management, scientific achievements transformation and spatiotemporal multidimensional visualization, under a unified highly-intensified framework. Through three years of hard work, MDRMP was initially built and has been put into operation, providing professional services for decision makers and other stakeholders with real-time disaster monitoring, early warning, impact analysis and risk assessment. The main functions of MDRIMP include hazard identification, risk prediction, risk regionalization, warning service, information inquiry, online analysis, etc.<br>MDRMP contains four subsystems, namely, Big Data Application Center, Model and Algorithm Center, Online Analysis Center and Operation Center. Big Data Application Center include 12 major categories, more than 600 million various pieces of information. Based on the Cloud-terminal and GIS technology, the multi-source and heterogeneous data is jointed in horizontal direction and correlated in vertical direction with its spatial attributes, forming the core database of the whole system. Model and Algorithm Center integrated more than 100 models of the algorithm related to disaster risk analysis. The algorithm library realizes the unified scheduling, management and real-time monitoring through registration, classification and execution monitoring technologies.<br></span>MDRMP has already been applied nationwide based on a Cloud-terminal, and support unified access, personalized configuration and service customization of users in provinces, cities and counties in China. This paper provides an overview, functions and the current status of the MDRMP. It will also describe how services are made available to the end user via various channels in addition to the productions of MDRMP in routine operations.</p>

Climate Services for Meteorological Disaster Risk Reduction in China

2020 ◽  
Author(s):  
Lianchun Song ◽  
Yujie Wang
Keyword(s):  
Climate Change ◽  
Risk Management ◽  
Risk Reduction ◽  
Disaster Risk Reduction ◽  
Disaster Risk ◽  
Decision Makers ◽  
Disaster Risk Management ◽  
Climate Services ◽  
Meteorological Disaster ◽  
Meteorological Disasters

<p><strong>ABSTRACT</strong></p><p>  China belongs to monsoon climate suffering from a wide-range of meteorological disasters such as flood, drought, typhoon, heat wave, frost, haze, sandstorm and etc. Many of these disasters have become more frequent and resulted in more significant impacts on socio-economy development in China in recent decades, and this can be attributed to climate change in part. From 1984 to 2018, the average annual direct economic loss caused by meteorological disasters reached $29 billion, accounting for 1.8% of the GDP coupled with a death toll of up to 3710 people. It is of major national importance to provide high-quality, useable climate services to help manage and reduce the risk of meteorological disasters, as well as to aid sustainable development.</p><p>We describe the climate services for the whole cycle of disaster risk management including risk identification, risk warning, disaster prevention, restoration and reconstruction in China. Based on the practices of National Climate Center(NCC) of China Meteorological Administration, we summarize the benefits, experiences and challenges of climate services for meteorological disaster risk reduction in China.</p><p>Firstly, identifying and understanding climate risks are fundamental for effective disaster risk management. In addition to short term risk management, such climate services assist in building long term resilience through restoration and reconstruction which focus on reducing the underlying risk factors, siting critical infrastructure, transferring risks and strengthening disaster preparedness capacity. Secondly, China has established successful working approaches, such as government leadership, coordination among different sectors, and participation from key communities, to more effectively manage disasters. Thirdly, capacity building of climate services for disaster risk reduction is very important. NCC has established a climate impact assessment service platform including comprehensive climate risk assessment indicators, quantitative assessment of the scope, intensity, duration and losses in meteorological disasters. These services are tailored to decision-making for the effective management of disasters for society. Finally, we discuss the challenges of climate services for disaster risk reduction. Many decision-makers in climate sensitive sectors have insufficient awareness of their vulnerability to future climate change. In fact, decision-makers would benefit from better understandings of climate-related hazards and impacts. A more comprehensive assessment of the risk of meteorological-related disasters needs undertaking, along with an analysis of the vulnerability of the hazard-affected system and interactions between meteorological-related disasters and socio-economic systems.</p>

scholarly journals Health Workforce Development in Health Emergency and Disaster Risk Management: The Need for Evidence-Based Recommendations

2021 ◽  
Vol 18 (7) ◽  
pp. 3382
Author(s):  
Kevin K. C. Hung ◽  
Sonoe Mashino ◽  
Emily Y. Y. Chan ◽  
Makiko K. MacDermot ◽  
Satchit Balsari ◽  
...  
Keyword(s):  
Risk Management ◽  
Risk Reduction ◽  
Case Studies ◽  
Workforce Development ◽  
Health Workforce ◽  
Disaster Risk Reduction ◽  
Disaster Risk ◽  
Disaster Risk Management ◽  
Evidence Based ◽  
Literature Reviews

The Sendai Framework for Disaster Risk Reduction 2015–2030 placed human health at the centre of disaster risk reduction, calling for the global community to enhance local and national health emergency and disaster risk management (Health EDRM). The Health EDRM Framework, published in 2019, describes the functions required for comprehensive disaster risk management across prevention, preparedness, readiness, response, and recovery to improve the resilience and health security of communities, countries, and health systems. Evidence-based Health EDRM workforce development is vital. However, there are still significant gaps in the evidence identifying common competencies for training and education programmes, and the clarification of strategies for workforce retention, motivation, deployment, and coordination. Initiated in June 2020, this project includes literature reviews, case studies, and an expert consensus (modified Delphi) study. Literature reviews in English, Japanese, and Chinese aim to identify research gaps and explore core competencies for Health EDRM workforce training. Thirteen Health EDRM related case studies from six WHO regions will illustrate best practices (and pitfalls) and inform the consensus study. Consensus will be sought from global experts in emergency and disaster medicine, nursing, public health and related disciplines. Recommendations for developing effective health workforce strategies for low- and middle-income countries and high-income countries will then be disseminated.

scholarly journals Big Data Analytic Framework for Organizational Leverage

2021 ◽  
Vol 11 (5) ◽  
pp. 2340
Author(s):  
Sanjay Mathrani ◽  
Xusheng Lai
Keyword(s):  
Big Data ◽  
Web Sites ◽  
Big Data Analytics ◽  
Building Blocks ◽  
Application Service ◽  
Data Application ◽  
Other Information ◽  
Big Data Application ◽  
Diverse Data ◽  
Framework System

Web data have grown exponentially to reach zettabyte scales. Mountains of data come from several online applications, such as e-commerce, social media, web and sensor-based devices, business web sites, and other information types posted by users. Big data analytics (BDA) can help to derive new insights from this huge and fast-growing data source. The core advantage of BDA technology is in its ability to mine these data and provide information on underlying trends. BDA, however, faces innate difficulty in optimizing the process and capabilities that require merging of diverse data assets to generate viable information. This paper explores the BDA process and capabilities in leveraging data via three case studies who are prime users of BDA tools. Findings emphasize four key components of the BDA process framework: system coordination, data sourcing, big data application service, and end users. Further building blocks are data security, privacy, and management that represent services for providing functionality to the four components of the BDA process across information and technology value chains.

Preliminary Benefits of Big Data in the Construction Industry: A Case Study

2022 ◽  
pp. 1-11
Author(s):  
Bernard Tuffour Atuahene ◽  
Sittimont Kanjanabootra ◽  
Thayaparan Gajendran
Keyword(s):  
Big Data ◽  
Construction Industry ◽  
Construction Projects ◽  
Big Data Applications ◽  
Data Application ◽  
Construction Firm ◽  
Big Data Application ◽  
Tangible Benefit ◽  
Design Construction

Big data applications consist of i) data collection using big data sources, ii) storing and processing the data, and iii) analysing data to gain insights for creating organisational benefit. The influx of digital technologies and digitization in the construction process includes big data as one newly emerging digital technology adopted in the construction industry. Big data application is in a nascent stage in construction, and there is a need to understand the tangible benefit(s) that big data can offer the construction industry. This study explores the benefits of big data in the construction industry. Using a qualitative case study design, construction professionals in an Australian Construction firm were interviewed. The research highlights that the benefits of big data include reduction of litigation amongst projects stakeholders, enablement of near to real-time communication, and facilitation of effective subcontractor selection. By implication, on a broader scale, these benefits can improve contract management, procurement, and management of construction projects. This study contributes to an ongoing discourse on big data application, and more generally, digitization in the construction industry.

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