Abstract
This research aims to explore the spatial pattern of vulnerability and resilience to natural hazards in northeastern Taiwan. We apply the spatially explicit resilience-vulnerability model (SERV) to quantify the vulnerability and resilience to natural hazards, including flood and debris flow events, which are the most common natural hazards in our case study area due to the topography and precipitation features. In order to provide a concise result, we apply the principal component analysis (PCA) to aggregate the correlated variables. Moreover, we use the spatial autocorrelation analysis to analyze the spatial pattern and spatial difference. We also adopt the geographically weighted regression (GWR) to validate the effectiveness of SERV. The result of GWR shows that SERV is valid and unbiased. Moreover, the result of spatial autocorrelation analysis shows that the mountain areas are extremely vulnerable and lack enough resilience. In contrast, the urban regions in plain areas show low vulnerability and high resilience. The spatial difference between the mountain and plain areas is significant. The topography is the most significant factor for the spatial difference. The high elevation and steep slopes in mountain areas are significant obstacles for socioeconomic development. This situation causes consequences of high vulnerability and low resilience. The other regions, the urban regions in the plain areas, have favorable topography for socioeconomic development. Eventually, it forms a scenario of low vulnerability and high resilience.
Highlights
The concept of vulnerability and resilience to natural hazards has been applied in the field of disaster management
Compared to other administrative areas in eastern Taiwan, our case study area has more opportunities for socioeconomic development because it is closely adjacent to Taipei
The topography plays an essential role in the distribution of exposure, sensitivity, and adaptive capacity
Summary
The concept of vulnerability and resilience to natural hazards has been applied in the field of disaster management. Multiple models and indicators have been developed and applied to investigate the vulnerability and resilience to natural hazards [1,2]. Spatial differences and spatial patterns are unneglectable factors because human is one of the important subjects of disaster events. Characteristics of humans, such as age, wealth, and occupation, are highly variable spatially. Humans create a spatial difference to affect the vulnerability and resilience to natural hazards [3,4]. The spatial difference significantly influences the vulnerability and resilience to natural hazards. Environmental factors, such as topography, have a significant influence on humans and spatial differences [4]
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