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Data Integration and Analysis System (DIAS) Contributing to Climate Change Analysis and Disaster Risk Reduction
Author(s) -
Akiyuki Kawasaki,
Akio Yamamoto,
Petra Koudelova,
Ralph Allen Acierto,
Toshihiro Nemoto,
Masaru Kitsuregawa,
Toshio Koike
Publication year - 2017
Publication title -
data science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.358
H-Index - 21
ISSN - 1683-1470
DOI - 10.5334/dsj-2017-041
Subject(s) - disaster risk reduction , resilience (materials science) , climate change , sustainable development , computer science , risk analysis (engineering) , emergency management , environmental resource management , business , political science , environmental science , ecology , physics , biology , law , thermodynamics
In 2015, global attempts were made to reconcile the relationship between development and environmental issues. This led to the adoption of key agreements such as the Sustainable Development Goals. In this regard, it is important to identify and evaluate under-recognized disaster risks that hinder sustainable development: measures to mitigate climate change are the same as those that build resilience against climate-related disasters. To do this we need to advance scientific and technical knowledge, build data infrastructure that allows us to predict events with greater accuracy, and develop data archives. For this reason we have developed the Data Integration and Analysis System (DIAS). DIAS incorporates analysis, data and models from many fields and disciplines. It collects and stores data from satellites, ground observation stations and numerical weather prediction models; integrates this data with geographical and socio-economic information; then generates results for crisis management of global environmental issues. This article gives an overview of DIAS and summarizes its application to climate change analysis and disaster risk reduction. As the article shows, DIAS aims to initiate cooperation between different stakeholders, and contribute to the creation of scientific knowledge. DIAS provides a model for sharing transdisciplinary research data that is essential for achieving the goal of sustainable development

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