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

Abstract: 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, National Climate Center of China developed a Meteorological disaster risk management platform (MDRIMP), 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, MDRIMP 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.

MDRIMP 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.

MDRIMP 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 MDRIMP. It will also describe how services are made available to the end user via various channels in addition to the productions of MDRIMP in routine operations.

Keywords: disaster risk, big data, algorithm library, cloud-terminal integrated GIS