Socio-economic vulnerability assessment at building scale: A case study in Youngsan watershed, South Korea

Despite the growing efforts in quantifying disaster vulnerability, its assessment at the building scale remains a challenge. In this study, we aim to quantify the socio-economic vulnerability index (SEVI) for every building by combining its housing price data with SEVI values at sub-district level. The methodology consists of three main steps. First, the latest social and economic data from Gwangju and Jeollanam provinces of Youngsan watershed were collected at sub-district and district levels. These data served as inputs for the Principal Component Analysis (PCA) algorithm to compute SEVI at sub-districts level. Second, housing price data were gathered for as many residential buildings as possible and combined with the SEVI values of their associated sub-districts. This combination was conducted with an assumption that households with more expensive housing are less vulnerable to natural disasters. Finally, a geocoding technique was adopted to tranform physical addresses into geospatial locations, enabling the assignment of vulnerability values into building polygons for further analysis and visualization. The outcome of this study is a map detailing the vulnerability levels of individual buildings. The main findings reveal that (1) the Southeastern part of Youngsan watershed tends to be more vulnerable to disaster, with sub-districts exhibiting high SEVI levels mostly located near the Youngsan River; (2) sub-districts with the highest number of highly vulnerable buildings tend to have only medium SEVI levels. By integrating these insights into disaster risk mitigation efforts, policymakers can develop more detailed and effective strategies for both short and long term, focusing on each building individually.

 

Acknowledgement

This study was supported by Korea Environment Industry & Technology Institute (KEITI) through R&D Program for Innovative Flood Protection Technologies against Climate Crisis Program (or Project), funded by Korea Ministry of Environment(MOE)(RS-2023-00218873).