Integrating traditional knowledge and cultural heritage with climate adaptation and disaster risk reduction: the role of training and tools

IF 1.1 Q4 GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY
Sanjaya Bhatia, Nidhi Shukla
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引用次数: 0

Abstract

PurposeThis paper investigates potential solutions to the challenges governments and stakeholders face in applying climate change adaptation and disaster risk reduction actions in ways that will save lives and use funds efficiently. The paper examines how traditional knowledge and cultural heritage can improve resilience and assesses the potential impact of relevant tools and training. Successful examples of tools, and applications of traditional knowledge as an accelerator to enhanced resilience will be explored.Design/methodology/approachThe paper studies the importance of integrating cultural heritage with climate and disaster risk reduction plans and examines why this has not been happening to the extent it should. While probing the barriers to such integration, the paper also explores examples of best practice drawn from experience gathered in ICCROM projects. Possible mechanisms to overcome common barriers through training are suggested, and the role that training and relevant tools could play in enabling and accelerating such integration are studied.FindingsThe conclusions demonstrate that training is a critical factor in facilitating the knowledge enhancement needed to understand how to integrate disaster and climate risks.Originality/valueThe research was conducted as part of a training program which the authors helped organize. The analysis is the original work of the authors.
将传统知识和文化遗产与适应气候和减少灾害风险相结合:培训和工具的作用
目的 本文探讨了政府和利益相关方在以拯救生命和有效利用资金的方式开展适应气候变化和减少灾害风险行动时所面临挑战的潜在解决方案。本文探讨了传统知识和文化遗产如何提高抗灾能力,并评估了相关工具和培训的潜在影响。设计/方法/途径 本文研究了将文化遗产与气候和灾害风险降低计划相结合的重要性,并探讨了这一工作尚未达到应有程度的原因。在探究这种整合的障碍的同时,本文还探讨了从国际文化财产保护与修复研究中心(ICCROM)项目经验中汲取的最佳实践范例。本文提出了通过培训克服常见障碍的可能机制,并研究了培训和相关工具在促进和加快这种整合方面可以发挥的作用。研究结论表明,培训是促进知识提升的关键因素,而知识提升是了解如何整合灾害和气候风险所必需的。分析是作者的原创性工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.90
自引率
10.00%
发文量
63
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