GSNL 2.0: leveraging on Open Science to promote science-based decision making in Disaster Risk Reduction
Abstract
In 2010 the GEO Geohazard Supersites and Natural Laboratories initiative (GSNL) launched the concept of a global partnership among the geophysical scientific community and the satellite and in situ data providers, aiming to promote scientific advancements in the knowledge of seismic and volcanic phenomena. The initial goal was successfully achieved, and many more new scientific results were obtained than it could have been possible if the Supersites had not existed (http://www.earthobservations.org/gsnl.php). At the same time the Supersites have demonstrated to be able to effectively support the rapid transfer of useful scientific information to the risk managers, exploiting the existing institutional relationships between the Supersite coordinators and the local decision makers. However, a more demanding call for action is given by the Sendai Framework 2015-2030 (outcome of the 2015 UN World Conference on Disaster Risk Reduction), where for the first time the knowledge of the risk components and the science based decision-making process are defined as top priorities for an effective DRR. There are evident possible synergies between the Sendai framework, GEO, the CEOS (Committee on Earth Observation Satellites), and GSNL, but for maximum benefit and effectiveness the latter needs to progress at a faster pace towards a full implementation of the Open Science approach to geohazard science. In the above global framework the Supersites can represent local test beds where to experiment coordination, collaboration and communication approaches and technological solutions tailored to the local situation, to ensure that the scientific community can contribute the information needed for the best possible decision making. This vision and the new developments of GSNL 2.0 have been approved by the GEO Program Board, and a clear roadmap has been set for the period 2017-2019. We will present the approach and the implementation plan at the conference.
- Publication:
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EGU General Assembly Conference Abstracts
- Pub Date:
- April 2017
- Bibcode:
- 2017EGUGA..1910550S