A literature review of dual disaster challenges for resilient office building toward reducing disaster risks
Flood is acknowledged as the most common natural disaster in several parts of the globe. For Malaysia, flood is considered as the most frequent natural disaster, with the frequency of at least once a year. The risks of flood can be seen through property loss and damages, infrastructure casualties, a...
Saved in:
Main Authors: | , , |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/98896/1/SitiUzairiahMohd2022_ALiteratureReviewofDualDisaster.pdf http://eprints.utm.my/id/eprint/98896/ http://dx.doi.org/10.1088/1755-1315/1082/1/012021 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Flood is acknowledged as the most common natural disaster in several parts of the globe. For Malaysia, flood is considered as the most frequent natural disaster, with the frequency of at least once a year. The risks of flood can be seen through property loss and damages, infrastructure casualties, and disruption to socio-economic activities. Adding to that, Malaysia also faced the flood during the pandemic when it hit several states, namely Pahang, Johor, and Kelantan, during the monsoon season in 2020 and 2021, amid the rising cases of Covid-19. The ongoing COVID-19 pandemic has posed significant challenges for disaster response, calling for the new norms to be quickly established for better disaster risk reduction. Several mitigation strategies have been taken by the government to reduce the risks of floods in Malaysia. As office buildings possess important roles in delivering effective services to the public while maintaining their critical documents, this paper focuses on providing related literature on building resilience. Having an early understanding of the core elements of office building resilience in dual disaster challenges will provide the basis for further investigation in the later stage of data collection. |
---|