Post-disaster reconnaissance is vital for assessing the impact of a natural disaster on the built environment and informing improvements in design, construction, risk mitigation, and our understanding of extreme events. The data obtained from reconnaissance can also be utilized to improve disaster recovery planning by maximizing resource efficiency, minimizing waste, and promoting resilience in future disasters. This paper aims to investigate existing reconnaissance reports and datasets to identify the factors that impact the reusability of buildings post-disaster and to recommend strategies that align with circular economy goals. The study adopted a three-step research methodology to attain the proposed goals: (1) thematic analysis was used to evaluate types of damages reported in the reconnaissance reports; (2) a supervised machine-learning algorithm was employed to analyze reconnaissance datasets; and (3) a concept map was developed based on interviews of 109 stakeholders in disaster-prone communities to recommend strategies to adopt circular economy practices post-disaster. The study results highlight the recurring risks of damage to different parts of the building and how circular economy resilience practices like deconstruction can minimize waste and maximize resource efficiency during post-disaster recovery. The findings of the study promote a more regenerative economy to build resilience to the challenges of future extreme weather events.
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Post Disaster Reconnaissance Studies of Landslides in India: Current Practices and Opportunities
Recently, India has witnessed several extreme rainfall events that caused moderate to severe landslides. However, extreme landslide events and their impacts can be mitigated by implementing effective preventive measures and policies derived from well-documented reports. Systematic and efficient post-disaster reconnaissance practices coupled with imagery-based technologies are essential for collecting perishable data and detailed geo-disasters documentation. A review of the current practices that are being implemented globally for acquiring spatial-temporal information using advanced technologies is presented. To this end, research articles, reconnaissance, and social media reports of a few notable extreme landslide events, namely 2013 Uttarakhand India, 2015 Kfarnabrakh Lebanon, 2018 Hokkaido Japan Eastern, were summarized. The best practices for future landslide reconnaissance studies in India, including the benefits of methodically acquiring and archiving photographic imagery using mobile devices and cloud apps, are presented.
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- Award ID(s):
- 1826118
- PAR ID:
- 10338232
- Editor(s):
- F. Vahedifard
- Date Published:
- Journal Name:
- ASCE Geo-Extreme
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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