Information Management

Disaster management team in front of a burned shop in New Delhi, India (2021)
Climate intelligence can help businesses monitor their exposure to climate risk more accurately.
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This article utilizes the Sendai Framework for Disaster Risk Reduction as an illustrative case to identify and interrogate ten selected notable truisms, from across the social and natural sciences.
Emphasizing uncertainty in model projections of long-term sea level rise is a misguided approach. Instead, we should focus on communicating what we do know while improving model confidence.
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This paper aims to identify state-of-the-art data sources for building damage assessment and provide guidance for more efficient data collection. Earthquakes are one of the most catastrophic natural phenomena.
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This article is an exploratory mapping exercise of and a collective reflection on Sustainable Development Goals and on the Sendai Framework's indicators—and their use in measuring progress towards disaster risk reduction.
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This report is a compilation of achievements and results to date, from the World Bank Crisis & Disaster Risk Finance Analytics program, on the integration of earth observation, big data, machine learning and artificial intelligence for disaster risk finance.
Drawing on recent research, Simon Addison and Sam Barrett explain why disaster displacement risk assessments must integrate better quality data on the specific vulnerabilities of different people to escalating climate risks.
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 This study explores the implications of the frequency of the Korean Public Alert Service (KPAS) through an online survey. Since 2005, the South Korean government has been using the service to issuing emergency alerts to mobile devices.
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This paper assesses mobile alert and warning in the United States and Japan by confronting the challenges of international harmonization. A U.S.-Japan expert workshop on mobile alert and warning was held online 8–10 September 2021.