<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Coastal areas are the most developed areas in China’s economic society, but they are vulnerable to storm surges. The characteristics of coastal cities under the influence of storm surges can be targeted to adjust social and economic activities and promote sustainable development. Combining characteristics of 52 coastal cities and based on the indicator system method and data cluster analysis, this study explores the different indicators and future development strategies of 5 clusters of cities when facing storm surges, aiming to fill the research gap in this area. The indicators related to the economy, population, and environment of coastal cities were selected, and the characteristics and frequency of regional storm surges were considered. At the same time, the K-means clustering method and DBSCAN were used to select the most suitable clustering method. The clustering results of coastal cities caused by storm surge disasters were analyzed, and a series of specific strategies and suggestions were proposed. According to the research findings, the K-means clustering method is more appropriate for this study. A total of 52 cities are clustered into five categories, of which the number of the fourth category is the largest, and the number of the fifth category is the least. The findings can be used to scientifically determine and guide subsequent analyses related to the disaster-bearing abilities of different types of coastal cities in the face of storm surges, thereby greatly enhancing and strengthening refined storm surge disaster defense efforts.</p>
</abstract>

Coastal areas are the most developed areas in China’s economic society, but they are vulnerable to storm surges. The characteristics of coastal cities under the influence of storm surges can be targeted to adjust social and economic activities and promote sustainable development. Combining characteristics of 52 coastal cities and based on the indicator system method and data cluster analysis, this study explores the different indicators and future development strategies of 5 clusters of cities when facing storm surges, aiming to fill the research gap in this area. The indicators related to the economy, population, and environment of coastal cities were selected, and the characteristics and frequency of regional storm surges were considered. At the same time, the K-means clustering method and DBSCAN were used to select the most suitable clustering method. The clustering results of coastal cities caused by storm surge disasters were analyzed, and a series of specific strategies and suggestions were proposed. According to the research findings, the K-means clustering method is more appropriate for this study. A total of 52 cities are clustered into five categories, of which the number of the fourth category is the largest, and the number of the fifth category is the least. The findings can be used to scientifically determine and guide subsequent analyses related to the disaster-bearing abilities of different types of coastal cities in the face of storm surges, thereby greatly enhancing and strengthening refined storm surge disaster defense efforts.

Study on the Cluster of Coastal Cities in China under the Influence of Storm Surges

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Coastal areas are the most developed areas in China’s economic society, but they are vulnerable to storm surges. The characteristics of coastal cities under...

Study on the Cluster of Coastal Cities in China under the Influence of Storm Surges

Pubblicato online: 11 dic 2023

Pagine: -

Ricevuto: 22 feb 2023

Accettato: 21 giu 2023

DOI: https://doi.org/10.2478/amns.2023.2.01446

Parole chiave
Coastal cities, Storm surges, Indicator system, Cluster, k-means

© 2023 Li Zhu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Study on the Cluster of Coastal Cities in China under the Influence of Storm Surges

Pubblicato online: 11 dic 2023

Pagine: -

Ricevuto: 22 feb 2023

Accettato: 21 giu 2023

DOI: https://doi.org/10.2478/amns.2023.2.01446

Parole chiaveCoastal cities, Storm surges, Indicator system, Cluster, k-means

© 2023 Li Zhu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Coastal cities, Storm surges, Indicator system, Cluster, k-means