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Development of a global data poverty index and disaster risk reduction applications in coastal regions by means of free geoinformatic

Student thesis: Doctoral Thesis

This thesis examines the nature of freely available geospatial software and data in the context of disaster risk reduction and disaster management. The use of geospatial data is crucial to effective disaster management, from preparedness to response and recovery. The best methodologies and technologies are useless if they cannot be accessed and used by the people in need or interested. Global inequalities in the provision and use of digital data and information – the so-called Digital Divide - are examined by means of datasets from 2009 to 2013. Subsequently an innovative Data Poverty Index is presented as a metric to compare differences worldwide. The focus of the presented method is on the incorporation of information and communication technology variables; also considered are the number of people in a country who can make use of freely available digital resources due to their education, access to the Internet and required hardware. A significant contribution is the clear indication that the gap between the data-poor and the data-rich is currently widening.
The highest population growth until 2050 is expected in developing countries, especially in Africa and Asia, the majority of them with coastlines. Therefore, the focus of this research is on coastal regions and methods that can be applied in developing countries. Having methods, data and software in place that can improve vulnerability mapping and highlight at-risk areas, helps to focus limited financial and expert resources. Although applied geoinformatics has demonstrated great potential for disaster risk reduction applications, only in recent years there has been a substantial shift away from crisis response towards disaster preparedness and mitigation. A free geoinformatics approach, combined with freely available training materials could assist the development of sustainable disaster management, which is advocated by the United Nations Sendai Framework for Disaster Risk reduction. A number of low-cost geoinformatics case studies, covering the Caribbean, the UK, Sierra Leone and Sri Lanka, demonstrate the potential of free geoinformatics as well as highlighting some limitations.
Original languageEnglish
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Award dateSep 2015

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