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Perspectives of a global, dynamic exposure model for geo-risk assessment from remote sensing to crowd-sourcing
20 September 2016
Source
The GFZ German Research Centre for Geosciences
United Nations Office for Disaster Risk Reduction
The aim of the paper is to assess the challenge of implementing a global exposure model for different geo-hazards at the global scale within a dynamic, scalable framework. A global exposure model able to evolve would lay the basis for global vulnerability and risk assessment by providing reliable, standardised information on the exposed assets across a vast range of hazards.
The authors make the following recommendations to sketch a road-map towards the effective implementation of global, dynamic exposure databases (p. 20):
- A stronger collaborative effort among the world´s disaster risk reduction institutions is advocated to implement a unified exposure taxonomy, largely independent on the particular hazard.
- Rapid, large-scale data collection based on remote sensing should be fully exploited and whenever possible be integrated with in-situ information, employing multi-source and scale data sampling methodologies.
- Authoritative and non-authoritative sources should be integrated while ensuring quality standards and compliance with disaster risk reduction purposes.
- Exposure-collection should be regarded as a continuous process that is constantly evolving over space and time.
- Data and (statistical) models must coexist in a statistically sound framework in order to overcome the infeasibility of having a complete and fully enumerated global dynamic exposure database.
- Validation and quality assessment should be carefully assessed throughout the collection-description-dissemination process.
This document is an input paper of the 2015 Global Assessment Report on Disaster Risk Reduction.
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