<![CDATA[The UNISDR Sendai Framework for Disaster Risk Reduction hasthe stated outcome for “The substantial reduction of disaster riskand losses in lives, livelihoods and health and in the economic,physical, social, cultural and environmental assets of persons,businesses, communities and countries”. Priority 1 of theFramework, understanding disaster risk, requires policies andpractices for disaster risk management to be based on anunderstanding of disaster risk in all its dimensions ofvulnerability, capacity, exposure of persons and assets, hazardcharacteristics and the environment. In addition, complementaryschemes such as the Millennium Challenge Corporation, 100Resilient Cities and the UNISDR Disaster Resilient Scorecardalso have an essential requirement to identify, understand, anduse current and future risk scenarios. As natural hazards are acommon catalyst for disaster risk, understanding current andfuture risk scenarios requires detailed preliminary appraisals ofnatural hazard and risk scenarios, both at local and nationallevels, as detailed in the Sendai Framework. However, due to thedata-intense nature of such appraisals, undertaking them can beexpensive and time consuming, and thus hinder progress atmeeting the aims of Priority 1. As such, we here evaluate thepotential of available “Open Source” data, such asASTER/SRTM Digital Elevation Models (DEMs) andLandsat/Sentinel satellite imagery, coupled with a range ofprocessing techniques, for the cost and time effective screeningand preliminary assessment of a range of natural hazards.Despite the spatial resolution of these data being between 30 –50 m, the outputs provide an important preliminary assessmentof natural hazards, thus enabling policies and practices fordisaster risk management to be focused on areas of highsusceptibility and vulnerability. These methods are applicable tocommunities across the globe, but particularly to those withindeveloping countries that may be lacking alternative datasources]]>
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