1. Introduction
A tsunami is a sudden natural disaster with short duration, but it may have a lasting impact on the affected region. Although a large tsunami is a relatively rare event, it is one of the most devastating and deadly coastal disasters, often causing great loss of life. On 26 December 2004, the Indian Ocean tsunami [
1], with a maximum tsunami runup of 50.9 m, killed more than 220,000 people. This tsunami destroyed thousands of buildings, industries, bridges, and other manmade infrastructure, making it one of the most destructive tsunamis in history. The tsunami waves hit many countries around the Indian Ocean, causing great damage and leaving 1.5 million people homeless. The 2011 Japan tsunami [
2,
3,
4], with a tsunami runup of 38.9 m, killed 18,000 people. The tsunami, in combination with a series of disasters and accidents caused by it, resulted in devastating damage to parts of northeast Japan. Historically, there have been several major tsunami events, including the 1755 Lisbon tsunami [
5] and the 1964 Alaska Tsunami [
6]. In addition, tsunamis are also triggered by landslides and volcanic eruptions. Two non-seismic tsunamis have occurred since 2011, the 2018 Indonesia tsunami [
7] and the 2022 Tonga tsunami [
8].
Previous tsunami research has been conducted to understand the characteristics of tsunami hazard [
9,
10,
11,
12]. The management of future tsunami risk requires a good understanding of the disaster. According to natural disaster system theory, tsunami risk in a given region should take into account both the tsunami hazard and the tsunami vulnerability of the affected objects (population and infrastructure). Quantifying the vulnerability of affected objects is important for tsunami risk assessment. Tsunami risk assessment results could help to understand the impact of a tsunami before its arrival. In general, historical tsunami records are too limited to conduct a purely empirical disaster assessment. Therefore, tsunami risk assessment needs to use a combination of numerical modeling and observation data to assess tsunami risk. In the last two decades, tsunami risk assessment methods have experienced substantial growth. Two popular methods are the deterministic risk assessment [
13,
14] and the probabilistic risk assessment [
15]. The deterministic tsunami assessment considers the worst-case tsunami scenario, analyzes the tsunami hazard (wave height, inundation area, and flow velocity), and calculates the tsunami risk in combination with tsunami vulnerability. The worst-case earthquake scenarios are associated with seismic dip–slip motion [
16]. The probabilistic tsunami risk assessment considers all possible tsunami events to estimate the probability of a wave height at a particular location above a threshold level over a certain period. This method provides a likelihood of occurrence and return periods [
17].
In recent years, a substantial amount of research on new methods and technologies for tsunami risk assessment has been conducted. Some studies have highlighted the potential of remote sensing techniques in tsunami risk assessment [
18]. Since 2004, remote sensing has been used in many tsunami studies. Remote sensing technologies and data are used in combination with other data to analyze tsunami hazard, vulnerability, and risk. The application of remote sensing in tsunami risk assessment includes providing input for tsunami numerical calculations, tsunami damage monitoring, and tsunami vulnerability analysis. The bathymetry data derived from remote sensing can be used as input bathymetry data for tsunami numerical models. Land use data can be used to analyze coefficients of friction in tsunami models [
19]. Satellite images can also be used for rapid, large-scale damage detection to understand the scale of tsunamis, especially in affected areas that cannot be reached immediately after a tsunami disaster [
19]. A number of important input parameters for vulnerability analysis were derived from remote sensing [
20,
21].
Land use and land cover (LULC) is a classic concept and key parameter for understanding the relationship between humans and the environment [
22]. Remote sensing data are often used to monitor LULC change [
23,
24]. LULC changes are related to the catastrophic effects of disasters. Understanding changes in LULC and their regional distribution is critical to addressing a variety of environmental and natural disaster issues [
25]. Over the past half a century, more and more free satellite imagery data and improved classification technologies have been made available. The Landsat 8 satellite was launched in February 2013 and has provided data for nearly a decade [
26]. The new generation Landsat 9 satellite was launched in September 2021 [
27]. At present, the Operational Land Imager (OLI) and OLI2 sensors regularly observe the global land surface. The Landsat images with a resolution of 30 m have been widely used in ecosystem variation research [
28], disaster prevention and mitigation [
29], and detailed LULC mapping [
30] because of their rich archives and free availability [
31]. In previous literature, Landsat images and their spectral indices were often used for LULC classifications [
32].
With rapid global urbanization, the population living in coastal areas is increasing, and economic assets are becoming concentrated in the region. Tsunami risk change means the change in tsunami risk of a certain area over time. Paulik developed a spatiotemporal loss model to quantify the changes in tsunami risk to residential buildings over a 20-year period [
33]. Qidong County, located on the southeast coast of China, is facing the threat of both transoceanic and regional tsunamis, especially tsunamis from the Ryukyu Trench. The purpose of this paper is to analyze the change in tsunami risk for Qidong County, China, from 2013 to 2022, considering the worst tsunami scenario of Ryukyu Trench. LULC classification results were used to analyze tsunami vulnerability. Tsunami risk and risk change were analyzed in combination with tsunami hazard and tsunami vulnerability.
4. Discussion
With the ongoing rapid economic development, increasing numbers of people and important facilities are being concentrated in coastal areas. Tsunami risk and its temporal change require more attention. This study discussed the tsunami risk change in Qidong County from 2013 to 2022.
Our results suggest that the tsunami risk of Qidong County is generally high in cases of potential earthquakes in the Ryukyu Trench. Meanwhile, economic development and urbanization have led to an increase in tsunami risk. Hence, disaster prevention and mitigation efforts need to be strengthened to address increased tsunami risk in Qidong County. Relevant tsunami mitigation measures need to be developed, including strengthening tsunami risk assessments, conducting research on disaster prevention measures for important disaster affected objects, and formulating tsunami emergency and evacuation plans in advance.
This paper has several limitations. (1) This paper analyzed the change in tsunami risk based on change in land use and vulnerability, assuming that tsunami inundation remains unchanged. Tsunami risk change with a change in inundation areas needs to be analyzed in the future. (2) The Landsat imagery used in this paper is a long-term data source available at present. Data sources with higher resolution will be considered in the future. (3) This study used the land use factor to analyze the change in tsunami vulnerability and tsunami risk. However, tsunami vulnerability involves some other factors, such as ecological vulnerability, economic vulnerability, and social vulnerability. More vulnerability factors could be considered to analyze tsunami risk change.
5. Conclusions
This study analyzed the tsunami risk change in Qidong County based on LULC classification. The tsunami hazard was evaluated by analyzing three magnitude 9.0 earthquakes in the Ryukyu Trench. Tsunami inundation was calculated using a tsunami numerical model. Tsunami hazard analysis defined the spatial scope of tsunami risk analysis.
Remote sensing was used for tsunami vulnerability analysis. The RF method, which was used for LULC classification, enabled rapid and accurate modeling based on sample training and analyzed LULC based on the model. A number of bands and spectral index combinations were tested to ensure the accuracy of land use classification. The analysis results show that the band combinations should be selected according to the month and season to improve the classification accuracy. In addition, suitable spectral indices could improve the accuracy of land use classification.
According to the results of LULC classification, built-up land in the inundation area of Qidong County increased by 16.62 km2 from 2013 to 2022. The risk change analysis results show that in the case of a magnitude 9.0 earthquake in the middle of the Ryukyu Trench, the area at tsunami risk level 1 in Qidong County increased by 4.57 km2 from 2013 to 2022. The area at tsunami risk level 1 area was along the coastal area. With the ongoing economic development of Qidong County, the coastal population and urbanization process have accelerated, resulting in the expansion of urban construction land and an increase in tsunami risk. Our method is important for tsunami disaster mitigation in Qidong County, and can also be applied to other regions with potential tsunami risk. This study conducted tsunami change analysis for five main land use types. However, if there is a children’s summer camp in the woodland, the tsunami risk will increase. Therefore, more detailed risk change analysis should be carried out in the future.
The occurrence of a tsunami disaster is inevitable, but the loss caused by disasters can be mitigated through reasonable disaster prevention measures. Tsunami mitigation awareness is an important part of tsunami disaster prevention. Educating the public about tsunami risk can popularize tsunami disaster observation and prevention, enhancing the public’s awareness of disaster prevention and mitigation. In addition, tsunami warning exercises should be carried out irregularly to practice the production and dissemination of tsunami warning information, in order to improve participation with tsunami warning institutions and government departments. Tsunami evacuation and other disaster responses should be studied. Tsunami evacuation plans should be developed and issued to help citizens cope with tsunami disasters.