Earth observations into action: the systemic integration of earth observation applications into national risk reduction decision structures

PurposeAs stated in the United Nations Global Assessment Report 2022 Concept Note, decision-makers everywhere need data and statistics that are accurate, timely, sufficiently disaggregated, relevant, accessible and easy to use. The purpose of this paper is to demonstrate scalable and replicable meth...

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Bibliographic Details
Published in:	Disaster prevention and management Vol. 32; no. 1; pp. 163 - 185
Main Authors:	Borges, David Eley, Ramage, Steven, Green, David, Justice, Christina, Nakalembe, Catherine, Whitcraft, Alyssa, Barker, Brian, Becker-Reshef, Inbal, Balagizi, Charles, Salvi, Stefano, Ambrosia, Vincent, San-Miguel-Ayanz, Jesus, Boschetti, Luigi, Field, Robert, Giglio, Louis, Kuhle, Laila, Low, Fabian, Kettner, Albert, Schumann, Guy, Brakenridge, G. Robert, Adler, Robert, Kontoes, Haris, De Boissezon, Helene, Eddy, Andrew, Kirschbaum, Dalia, Emberson, Robert, Cooley, Savannah, Lloyd, Simone, Blake, Cecille, Reichenbach, Kelsey
Format:	Journal Article
Language:	English
Published:	Langley Research Center Emerald Publishing Limited 14-06-2023 Emerald Emerald Group Publishing Limited
Subjects:	Agricultural production Agriculture Climate change Crops Decision making Disaster management Disaster risk Disasters Earth Earth Resources and Remote Sensing Emergency preparedness Floods Food security Frameworks Government Government agencies Humanitarianism Hunger International organizations Open data Pandemics Risk management Risk reduction Satellite observation Satellites Statistical analysis Statistical methods Sustainable development Work platforms Uganda Africa Geospatial Open science Disaster risk reduction Sendai framework Earth observations Earth Observations Sendai Framework Open Science Disaster Risk Reduction
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Summary:	PurposeAs stated in the United Nations Global Assessment Report 2022 Concept Note, decision-makers everywhere need data and statistics that are accurate, timely, sufficiently disaggregated, relevant, accessible and easy to use. The purpose of this paper is to demonstrate scalable and replicable methods to advance and integrate the use of earth observation (EO), specifically ongoing efforts within the Group on Earth Observations (GEO) Work Programme and the Committee on Earth Observation Satellites (CEOS) Work Plan, to support risk-informed decision-making, based on documented national and subnational needs and requirements.Design/methodology/approachPromotion of open data sharing and geospatial technology solutions at national and subnational scales encourages the accelerated implementation of successful EO applications. These solutions may also be linked to specific Sendai Framework for Disaster Risk Reduction (DRR) 2015–2030 Global Targets that provide trusted answers to risk-oriented decision frameworks, as well as critical synergies between the Sendai Framework and the 2030 Agenda for Sustainable Development. This paper provides examples of these efforts in the form of platforms and knowledge hubs that leverage latest developments in analysis ready data and support evidence-based DRR measures.FindingsThe climate crisis is forcing countries to face unprecedented frequency and severity of disasters. At the same time, there are growing demands to respond to policy at the national and international level. EOs offer insights and intelligence for evidence-based policy development and decision-making to support key aspects of the Sendai Framework. The GEO DRR Working Group and CEOS Working Group Disasters are ideally placed to help national government agencies, particularly national Sendai focal points to learn more about EOs and understand their role in supporting DRR.Originality/valueThe unique perspective of EOs provide unrealized value to decision-makers addressing DRR. This paper highlights tangible methods and practices that leverage free and open source EO insights that can benefit all DRR practitioners.
Bibliography:	Langley Research Center LaRC
ISSN:	0965-3562 1758-6100
DOI:	10.1108/DPM-09-2022-0186