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Integrating indigenous knowledge and state-of-the-art Earth observation solutions for the Sendai framework implementation
Disaster Prevention and Management ; 2023.
Article in English | Web of Science | ID: covidwho-2325568
ABSTRACT
PurposeIndigenous peoples represent one of the most vulnerable groups and need access as well as hands-on experience in the use of emerging Earth observations (EO)-based DRR solutions at the community level, while balancing this learning with traditional indigenous knowledge (IK). However, complicating any engagement between EO and IK is the reality that IKs are diverse and dynamic, with location-specific relevance and accuracy. Additionally, the COVID-19 pandemic caused complex risks and cascading effects for which the world was not prepared. Thus, there is a need to examine the lessons learned and motivate emerging EO-based innovations and demonstrations related to DRR and climate change adaptation.Design/methodology/approachHence, this study aims to undertake an in-depth assessment of IK related to DRR covering relevant UN instruments and provides state-of-the-art of opportunities presented by EO-based tools and solutions.FindingsThe overall research strategy was designed to integrate key components of IK for DRR in a coherent and logical way, with those offered by the EO technology developers and providers. There are several EO tools accessible that are relevant to integrate IK and complement DRR. The study examined and identified challenges and barriers to implement workable and replicable EO solutions in pursuit of resilience.Originality/valueThe key findings of this study will help create a balanced approach by acknowledging the importance of IK for DRR with co-development, co-creation and use of culturally relevant EO data and tools for sustainable innovation, capacity building and youth empowerment. The technological inequalities appear to be growing, and it would be challenging to meet the Sendai Framework indicators.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Language: English Journal: Disaster Prevention and Management Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Language: English Journal: Disaster Prevention and Management Year: 2023 Document Type: Article