自然灾害
弹性(材料科学)
社区复原力
多样性(控制论)
集合(抽象数据类型)
鉴定(生物学)
环境规划
自然灾害
环境资源管理
地理
计算机科学
环境科学
气象学
人工智能
物理
冗余(工程)
热力学
操作系统
植物
生物
程序设计语言
作者
Susan L. Cutter,Lindsey R. Barnes,Melissa M. Berry,Christopher G. Burton,Elijah Evans,Eric Tate,Jennifer Webb
标识
DOI:10.1016/j.gloenvcha.2008.07.013
摘要
There is considerable research interest on the meaning and measurement of resilience from a variety of research perspectives including those from the hazards/disasters and global change communities. The identification of standards and metrics for measuring disaster resilience is one of the challenges faced by local, state, and federal agencies, especially in the United States. This paper provides a new framework, the disaster resilience of place (DROP) model, designed to improve comparative assessments of disaster resilience at the local or community level. A candidate set of variables for implementing the model are also presented as a first step towards its implementation.
科研通智能强力驱动
Strongly Powered by AbleSci AI