TY  - JOUR
PY  - 2023//
TI  - A disaster-damage-based framework for assessing urban resilience to intense rainfall-induced flooding
JO  - Urban climate
A1  - Zhang, Xiwen
A1  - Mao, Feng
A1  - Gong, Zhaoya
A1  - Hannah, David M.
A1  - Cai, Yunnan
A1  - Wu, Jiansheng
SP  - e101402
EP  - e101402
VL  - 48
IS  - 
N2  - Resilience has been widely used as a concept to analyse, understand, and improve cities' coping capacities to disasters. However, it is still a challenge to operationalise and quantify resilience. This study proposes a framework for assessing resilience to disasters based on the relationship between disaster intensity and damage rate. We use intense (short-term heavy) rainfall-induced urban flooding in Shenzhen city, one of the largest cities in China, as an example to explore the main features and transferability of the proposed resilience assessment framework. In addition, we demonstrate the usability of the proposed framework by using it to assess and compare the effectiveness of two resilience-building strategies: (1) permeable pavement transformation and (2) land vulnerability reduction. This research makes an innovative contribution through its effective disaster-damage-based approach for quantitatively evaluating urban resilience to disasters, which can support building resilience and mitigating the impact of climate change.<p />  <p>Language: en</p>
LA  - en
SN  - 2212-0955
UR  - http://dx.doi.org/10.1016/j.uclim.2022.101402
ID  - ref1
ER  -