Building Local Resilience Platforms for Disaster Risk Reduction

Djalante, Riyanti, Bisri, Mizan, Fernandez, Glenn, Imai, Natsuko, Saito, Osamu and Okazaki, Kenji (2021). Building Local Resilience Platforms for Disaster Risk Reduction. United Nations University Institute for the Advanced Study of Sustainability.

Document type:
Report

Metadata
Documents
Versions
Statistics
  • Attached Files (Some files may be inaccessible until you login with your UNU Collections credentials)
    Name Description MIMEType Size Downloads
    UNU-IAS-PB-No22-2021.pdf UNU-IAS-PB-No22-2021.pdf application/pdf 144.07KB
  • Sub-type Policy brief
    Author Djalante, Riyanti
    Bisri, Mizan
    Fernandez, Glenn
    Imai, Natsuko
    Saito, Osamu
    Okazaki, Kenji
    Title Building Local Resilience Platforms for Disaster Risk Reduction
    Publication Date 2021-03
    Place of Publication Tokyo
    Publisher United Nations University Institute for the Advanced Study of Sustainability
    Pages 4
    Language eng
    Abstract As local communities are disproportionately impacted by disasters, there is an urgent need for multi-stakeholder platforms at the local level that can bring together knowledge and resources for resilience-building. Tackling challenges such as low governance capacity, lack of data and resources, and lack of community awareness requires building local platforms for disaster risk reduction (DRR), harnessing local academia, and developing local action plans through an inclusive approach. Recommendations: - Establish local platforms for direct engagement in DRR - Harness and directly engage with local universities as generators and disseminators of DRR knowledge - Promote inclusivity in building local disaster resilience
    Keyword Disaster risk reduction (DRR)
    Resilience building
    Copyright Holder United Nations University
    Copyright Year 2021
    Copyright type All rights reserved
    ISSN 24093017
  • Versions
    Version Filter Type
  • Citation counts
    Google Scholar Search Google Scholar
    Access Statistics: 1229 Abstract Views, 1110 File Downloads  -  Detailed Statistics
    Created: Mon, 22 Mar 2021, 15:42:36 JST by Rachel Nunn on behalf of UNU IAS