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3 results for “Disaster Risk Reduction”
Assessment of risk and vulnerability to disasters by field protocols and classification trees: an analysis of the Municipal Risk Reduction Plans (MRRP) of São Bernardo do Campo and Franco da Rocha (2020-2021), in Brazil
<p><span>Most disaster risk assessment methodologies were developed by natural science professionals. The UN Sendai Framework confirms the need to include these methods as interweaving complex networks of socially vulnerable financial processes, especially in developing countries. This work aimed to analyze the experience of including social vulnerability information in field protocols of the Municipal Risk Reduction Plans (MRRP) of São Bernardo do Campo and Franco da Rocha (2020-2021). A georeferenced database was structured with data from field protocols on risk sectors and then the relationship between vulnerability and risk was analyzed using the classification tree method. The results show that the geotechnical and social vulnerability variables relevant to risk attribution are largely overlapping over the sectors, but that the integrated analysis of the two dimensions allows a better interpretation of the risk level. However, the models with information from field protocols cannot replace a broader holistic assessment by the specialist in the field. Finally, qualitative reflections are made on the limitations and potential of including aspects of vulnerability in the specific case study.</span></p>
Data for: Spatial-temporal analysis of natural hazards and disasters in the Greater Horn of Africa between 2010 and 2024 to inform disaster risk reduction, and surveillance and control strategies for climate and environmentally sensitive diseases
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Mapping the exposure of tourism to weather extremes: The need for a spatially-explicit gridded dataset for disaster risk reduction
<p>This dataset contains the spatially-explicit gridded database based on social media data for over 150 different tourism-related classes that depicts tourism density (supply and demand) and perceived satisfaction in Europe, and the related exposure to selected climate extreme events. Information on tourism density (supply and demand) and perceived satisfaction are categorised for Attractions, Culinary, and Hospitality, while the exposure analysis of those clases are provided in separate, specific files. The provided dataset is made accessible to support large-scale and regional tourism research and extends its relevance to other fields that are part of tourism as a complex system, such as risk assessment and vulnerability studies. For citing this work, please refer to the research article "Mapping the exposure of tourism to weather extremes: The need for a spatially-explicit gridded dataset for disaster risk reduction", DOI 10.1088/1748-9326/ad3e91. Suggested citation: "Camatti, N., Hrast Essenfelder, A., & Giove, S. (2024). Mapping the exposure of tourism to weather extremes: The need for a spatially-explicit gridded dataset for disaster risk reduction. Environmental Research Letters."</p>
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