碎片
应急管理
数据收集
灾难恢复
环境资源管理
可持续发展
业务
计算机科学
环境规划
可持续管理
风险分析(工程)
持续性
环境科学
地理
政治学
操作系统
法学
气象学
统计
生物
数学
生态学
作者
Hiba Jalloul,Juyeong Choi,Nazli Yesiller,Derek C. Manheim,Sybil Derrible
标识
DOI:10.1016/j.resconrec.2022.106174
摘要
• Data needs for sustainable disaster debris management are identified. • Time-sensitive data are characterized using a four-phase planning framework. • Social network analysis is used to prioritize the collection of the identified data. • Effective reconnaissance methods are needed to capture important post-disaster data. Recycling and reuse are major components of disaster debris management with significant environmental, economic, and social benefits. To develop quantitative and sustainable debris management practices, a broad range of data is required. Existing studies have not comprehensively delineated the data and analysis requirements for quantitative assessment of sustainable debris management, which limits proper disaster data collection and restricts the development of approaches to efficiently quantify, characterize, and allocate disaster waste among existing and emerging debris management pathways. This study aimed to fill this gap by reviewing previous investigations to identify the data required to quantitatively assess both critical and practical aspects of sustainable disaster debris management. The literature review indicated that the most significant data for post-disaster debris management relate to i) the amount and composition of debris; ii) availability of temporary debris management sites; iii) hazards and environmental concerns; iv) economics; v) social considerations; and vi) funding policies. Considering the time-sensitive nature of different disaster debris data types, a four-phase planning framework is proposed for timely collection of data: pre-disaster, post-disaster response, short-term recovery, and long-term recovery. With significant identified data needs and finite amount of resources for data collection, particularly during post-disaster phases, social network analysis (SNA) is used to quantitively evaluate the relative importance of the data needs. Overall, it is recommended to develop comprehensive debris management inventories that aggregate diverse pre-disaster datasets, along with integrated specialized reconnaissance investigations to collect post-disaster data, most of which are identified as high priority.
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