Project Details
Abstract
The proposed research will support developing and developed states to build adaptive governance capabilities that will embed equitable disaster risk reduction and resilience in development planning and development programmes. We emphasize the importance of community involvement in disaster risk management planning and the role of legal principles and institutions in reducing asymmetries in knowledge and power within a society. In conditions of post-normal science, where facts and indicators are uncertain and values are disputed, there is need for a normative-institutional approach involving diverse stakeholders and the ponderation of legal principles. Our nexus-informed methodological approach combines artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) within a transdisciplinary research agenda. It will transform qualitative and quantitative data into actionable insights and inspire a new breed of disaster reduction governance. The project will do this by creating and applying an open-access tool, systematically eliciting expert views to contribute evidence to governments’ plans for disaster risk reduction, and developing response processes that integrate a normative institutional approach to support the legitimacy of any given intervention of policies intended to enhance the resilience of communities. This project will thereby develop innovative and implementable strategies and technologies to help reduce disaster risk and enhance societal coping capabilities. Appropriate policies and adaptive governance mechanisms will be discussed and negotiated with disaster planners, vulnerable communities and other stakeholders. International workshops and will ensure that lessons are learned from case studies and that best practices are identified, maximising knowledge exchange. The transdisciplinary outputs and guidelines will thus support decision-makers and communities to advance equitable disaster risk reduction through effective management of pre- and post-disaster risks placing vulnerable communities at the centre of all efforts.
Submitting Institute Name
Hamad Bin Khalifa University (HBKU)
| Sponsor's Award Number | BFC03-0630-190011 |
|---|---|
| Proposal ID | EX-QNRF-BFC-1 |
| Status | Finished |
| Effective start/end date | 1/05/20 → 1/06/23 |
Primary Theme
- None
Primary Subtheme
- None
Secondary Theme
- None
Secondary Subtheme
- None
Keywords
- Disaster risk reduction,Artificial intelligence,Resource nexus,Sustainable development,Equitable resilience
- None
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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Mapping Flood Exposure, Damage, and Population Needs Using Remote and Social Sensing: A Case Study of 2022 Pakistan Floods
Akhtar, Z., Qazi, U., Sadiq, R., El-Sakka, A., Sajjad, M., Ofli, F. & Imran, M., 30 Apr 2023, ACM Web Conference 2023 - Proceedings of the World Wide Web Conference, WWW 2023. Association for Computing Machinery, Inc, p. 4120-4128 9 p. (ACM Web Conference 2023 - Proceedings of the World Wide Web Conference, WWW 2023).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
12 Link opens in a new tab Citations (Scopus) -
Remote Sensing for Flood Mapping and Monitoring
Sadiq, R., Imran, M. & Ofli, F., 1 Jan 2023, International Handbook of Disaster Research. Springer Nature, p. 679-698 20 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
5 Link opens in a new tab Citations (Scopus) -
Towards fine-grained object-level damage assessment during disasters
Sadiq, R., Akhtar, Z., Peterson, S., Keegan, K., El-Sakka, A., Imran, M. & Ofli, F., 2023, In: Frontiers in Earth Science. 11, 990930.Research output: Contribution to journal › Article › peer-review
Open Access3 Link opens in a new tab Citations (Scopus)