Disaster Mitigation Measures Research Articles

Establishing a Landslide Traces Inventory for the Baota District, Yan’an City, China, Using High-Resolution Satellite Images

The Baota District of Yan’an City, located in the Loess Plateau, is an important patriotic education base in China. The region’s fragile geological environment and frequent geological disasters pose significant threats to the production and livelihood of residents. Establishing a landslide traces inventory can provide crucial assistance for studying regional land disaster distribution patterns and implementing disaster prevention and mitigation measures. However, the Baota District has not yet established a comprehensive and detailed landslide traces inventory, resulting in a lack of clear understanding and comprehensive knowledge regarding the threats and impacts of landslide disasters in the area. Therefore, this study employed high-resolution satellite images, applying a human–computer interactive visual interpretation method in conjunction with field survey verifications, to develop the most detailed and comprehensive landslide traces inventory for the Baota District to date. The results indicate that within the 3556 km2 area of the Baota District, there are 73,324 landslide traces, with an average landslide density of 20.62 km-2 and a total landslide area of 769.12 km2, accounting for 21.63% of the total land area. These landslides are relatively evenly distributed throughout the district, with a higher concentration in the east compared to the west. Most of the landslides are small in size. This study can support disaster prevention and mitigation efforts in the Baota District and serve as a reference for establishing landslide inventories in other regions of the Loess Plateau.

Assessment of waterlogging hazard during maize growth stage in the Songliao plain based on daily scale SPEI and SMAI

Waterlogging is one of the major disasters affecting crop yield and food security. The Songliao Plain, located in the mid-latitude region and known as the "Golden Maize Belt," is severely impacted by waterlogging, which significantly affects maize yield. Therefore, it is essential to conduct a detailed assessment of the waterlogging hazard for maize in the Songliao Plain and to apply the results to agricultural meteorological disaster prevention and mitigation measures. In this study, a comprehensive waterlogging hazard assessment index was constructed by combining environmental factors conducive to disaster and disaster-causing factors. Environmental factors included terrain slope, distance from rivers, and soil clay content, while disaster-causing factors included daily SPEI and SMAI during the maize growing season in the Songliao Plain from 1982 to 2020. The results indicate that: (1) The spatial distribution of waterlogging hazard in the Songliao Plain ranges from extremely high to extremely low, showing a gradual decrease from west to east. The western and southern parts of the Songliao Plain, such as Baicheng, Songyuan, Changchun, and Fuxin, are more prone to waterlogging disasters. (2) During different maize growth stages, the spatial distribution of high and extremely high levels of waterlogging hazard exhibited significant heterogeneity. There were notable differences in the duration of waterlogging around the year 2000, with a reduction in the duration of extremely high and high levels of waterlogging after 2000. (3) A Pearson correlation analysis was conducted between the comprehensive waterlogging hazard index and SIF (Solar-Induced Fluorescence) data during different maize growth stages. The results showed a strong correlation between the comprehensive waterlogging hazard index and SIF data, with the highest correlation coefficient reaching −0.9 and a p-value less than 0.05. The comprehensive maize waterlogging hazard index can be used for precise and timely assessment of waterlogging hazard during different growth stages of maize, and it has a positive impact on improving the ability to prevent and mitigate waterlogging risks.

Integration of the WRF model and IoT sensors to develop an early cold snap warning system for inland fishponds

The cold weather-related economic losses in the aquaculture and fisheries industries are enormous and will only increase due to future climate change. Advancements in weather forecasting have increased the accuracy of predicting environmental factors like air temperature, solar radiation, and wind speed. However, the water temperature of fishponds, which affects the lives of fish, cannot be accurately predicted. As a result, fishermen are unable to implement early disaster mitigation and avoidance measures effectively. In this study, we developed an early warning system for extreme temperature events in fishponds by using a weather forecasting model in combination with local observations from a customized sensor placed in a pond. This system could provide water temperature forecasts with up to 120 h of lead time. A fishpond and multiple events were selected to assess the performance. Compared to the actual observations, the predicted water temperature difference had a root mean square error of <2 °C for up to 72 h of lead time. Furthermore, due to limited computational resources for weather forecasting models, the water temperature and depth data collected by the sensor improved the accuracy of temperature prediction specific to each pond. The results have confirmed that the integrated method can effectively predict the water temperature of farmed fishponds and assist fishermen in implementing precautionary measures in time.

Assessing the district-level flood vulnerability in Bihar, eastern India: an integrated socioeconomic and environmental approach.

States of India like Bihar, Uttar Pradesh, and West Bengal along the Ganga River, endure natural disasters periodically, resulting in repeated trends of economic loss and damages. Especially, most of the districts of Bihar, India, are prone to floods. Based on this background, this study aims to assess the flood vulnerabilities across districts of Bihar, India, employing data from the Central Water Commission from 1953 to 2020. Further, we explore trends and patterns of loss and damage due to flood risks in Bihar. Using the flood vulnerability integrated method and the principal component analysis, the index is constructed by incorporating the three major indicators: exposure, sensitivity, and adaptive capacity. This study is unique, and advances from previous studies in using a greater number of variables in exposure indicator. The proxy variable for each indicator is identified through both inductive and deductive approaches, and the composite index is constructed using all three indicators. Also, we identify the districts with high level of education and per capita income are less likely to expose flood vulnerability. The comparison of the districts reflects wide range of variation in terms of flood vulnerability as per their adaptive capacity and sensitivity. Specifically, these findings align with Target Sustainable Development Goal 11.5. This study addresses the policy for disaster prevention, risk reduction, and mitigation measures, as well as the enhancement of the capability of adaptation to floods by the affected community.

Street Community-Level Urban Flood Risk Assessment Based on Numerical Simulation

Urban waterlogging is a serious urban disaster, which brings huge losses to the social economy and environment of the city. As an important means of urban rainfall inundation analysis, numerical simulation plays an important role in promoting the risk assessment of urban waterlogging. Scientific and accurate assessment of waterlogging disaster losses is of scientific significance for the formulation of disaster prevention and mitigation measures and the guidance of post-disaster recovery and reconstruction. In this study, the SCS-CN hydrological model and GIS coupling numerical simulation method were used to simulate the inundation of urban waterlogging under four different rainfall return periods and to realize the visualization of the inundation range and waterlogging depth in Zhengzhou. At the same time, based on the numerical simulation results, the building is used as the basic assessment unit to construct a refined assessment framework for urban waterlogging risk at the street community level based on hazard, exposure, and vulnerability analysis. The refined risk assessment results have an important reference value for optimizing the working ideas of waterlogging control and providing a reference for local management departments to effectively deal with waterlogging disasters.

The Influence of Students' Attribute on Earthquake Understanding in Klaten Regency

An earthquake is a type of natural disaster that cannot be predicted in terms of time or scale. Klaten Regency is one of the earthquake-prone areas of Indonesia. The occurrence of earthquakes in Klaten Regency has indeed surprised many parties. Implementing disaster mitigation measures is crucial in areas prone to disasters. Disaster mitigation education has been implemented in schools through intracurricular and extracurricular activities. This study aims to analyze (1) the student's understanding of earthquakes at the elementary, middle, and high school levels in Klaten Regency and (2) the impact of student attributes on an understanding of earthquakes. Students' Students comprise age and gender. This is a quantitative study with a correlational research approach. The study was 173 students from junior high school. Techniques for collecting data include questionnaires and documentation. Data analysis techniques employ descriptive statistics; furthermore, the tests used to answer the hypothesis are the Mann-Whitney test, kruskall Wallis, and Spearman rank. The Mann-Whitney test. According to the study results, (1) students' students' of earthquakes was 22% high, 75% moderate, and 3% low, and (2) The test results pointed out that student characteristics had no significant impact on students' student's knowledge.Keywords: Earthquake; Disaster; Students; Understanding of Disaster

Research on the economic loss prediction and vulnerability risk zoning of coastal erosion disaster: a case study from Liaoning, China

IntroductionCoastal erosion is widely distributed globally, with sandy coasts being particularly prominent, causing significant economic losses to coastal areas. This study focuses on the coastal areas of Liaoning Province, China, which represent typical sandy beach erosion.MethodsBased on the assessment of coastal erosion disaster losses, a multivariate variable-weight combination prediction model is utilized to predict the losses caused by coastal erosion disasters, providing an effective mathematical modeling approach for predicting such losses. Furthermore, the cluster analysis method is employed to delineate vulnerability risk zones for coastal erosion along the Liaoning Province coast.Results and discussionThe research findings indicate the following: (1) From 2023 to 2025, the losses due to coastal erosion disasters in Liaoning Province are projected to decrease significantly from a scale of 36 million RMB yuan to 5 million RMB yuan; (2) Based on the magnitude of disaster vulnerability risk, the coastal areas of Liaoning Province are categorized into four risk zones: high-risk zones (Jinzhou District), moderately high-risk zones (Zhuanghe City, Wafangdian City, Ganjingzi District), medium-risk zones (Lvshunkou District, Bayuquan), and low-risk zones (Gaizhou City, Suizhong County, Xingcheng City). Recommendations are proposed accordingly: (1) Effective measures should be implemented to mitigate the losses incurred by coastal erosion on land, buildings, infrastructure, agricultural output; (2) In the selection of disaster prevention and control measures,economic factors should be carefully considered in line with the specific circumstances of the losses. Specifically, the economic efficiency of disaster prevention and mitigation measures should be taken into account; (3) Precise efforts should be made to implement coastal erosion disaster prevention and control measures in different regions.

Comprehensive evaluation and optimal management of extreme disaster risk in Chinese urban agglomerations by integrating resilience risk elements and set pair analysis

This study comprehensively assesses the extreme disaster risk faced by Chinese urban agglomerations and optimizes disaster risk management strategies to enhance their disaster resilience and sustainable development. The focus is specifically on droughts, floods, and earthquakes. The integration of resilience risk elements and set pair analysis (SPA) is employed to obtain risk assessment results for different urban agglomerations, including hazard, exposure, vulnerability, and disaster prevention and mitigation capabilities. The study explores the contributions of important indicators, such as exposure, vulnerability, and disaster prevention and mitigation capabilities, in disaster risk assessment, as well as their performance in various risk-prone urban areas. Comparative analysis of the assessment results for different urban agglomerations under various disaster types reveals varying levels of risk in droughts, floods, and earthquakes across different regions. Some areas exhibit higher hazard, exposure, or vulnerability levels, necessitating strengthened disaster prevention and mitigation measures. Regions with high exposure, low vulnerability, and strong disaster prevention and mitigation capabilities may face lower earthquake disaster risk, while regions with low exposure, high vulnerability, and weak disaster prevention and mitigation capabilities may face higher earthquake disaster risk. Moreover, the Comprehensive SPA model and Interval-valued SPA model outperform traditional SPA methods in assessing the existing flood risk level in Chinese urban agglomerations. The integrated model plays a significant role in predicting earthquake disasters, demonstrating the best predictive performance. This study provides essential reference data for urban disaster prevention and mitigation efforts, aiming to enhance urban resilience and disaster resilience capabilities.

Study on Stability Analysis Method of Loess Slope Based on Catastrophe Theory – A Case Study of Loess Slope in Yili, Xinjiang

Based on the mutation theory, the paper studies the stability of loess slope, and discusses the loess slope in Yili region in Xinjiang. From the perspective of mechanics, the paper focuses on the influence of mutation phenomenon on the stability of loess slope, and deeply analyzes the mechanical mechanism in the mutation process. As an effective tool to study the phenomenon of discontinuous change, mutation theory has important applications in the stability analysis of loess slopes. By applying the mutation theory, the mutation characteristics of the loess slope in the Xinjiang Yili area were analyzed. In terms of mechanical mechanism, the stress distribution, deformation characteristics and the instability mode are discussed in detail. Through theoretical analysis and numerical simulation, it is found that when the slope stress reaches a certain critical value, mutation will occur, leading in a sharp decline of slope stability. Specific data show that in a typical loess slope in Yili area, when the stress reaches about 0.6 MPa, the slope changes, and the displacement instantly increases to more than twice the original, indicating that the slope has been in a state of instability. In the case study of loess slope in Yili, Xinjiang, the slope stability is comprehensively evaluated by combining field investigation to monitoring data and indoor test. By identifying and analyzing the mutation characteristics of the slope, it is found that there are widespread subsidence and disintegration problems in this area, which play a key role in the mutation process. The specific data show that the subsidence coefficient of the loess slope in Yili area is generally above 0.05, and the disintegration rate is more than 0.5% per hour. These factors jointly aggravate the mutation risk of the slope. Based on the above data analysis, the paper puts forward targeted disaster prevention and mitigation measures, including strengthening slope drainage, using appropriate reinforcement technology, etc. These measures aim to reduce the risk of mutation and improve the stability of the loess slope.

LandslideNet: A landslide semantic segmentation network based on single-temporal optical remote sensing images

Swiftly and accurately acquiring the spatial distribution, location, and magnitude of landslides while documenting them in a landslide cataloging database can furnish crucial information for precise disaster mitigation measures and secondary hazard prevention. The extraction of landslides using existing semantic segmentation algorithms may give rise to issues such as false detection and missed detection due to the diverse shape and texture features of landslides in remote sensing images, the abundance of spectral features, and the complexity of the environment. In this article, we proposed LandslideNet, a novel model specifically designed for accurate segmentation of landslides in single-temporal high spatial resolution optical remote sensing images. By constructing a landslide image dataset and employing the LandslideNet model, we successfully identify and segment landslides with high precision. Quantitative experimental results demonstrate that our LandslideNet achieves superior performance compared to widely used semantic segmentation models including U-Net, PSPNet, Deeplabv3+, HRNetv2, Segformer and GELAN-c with F1-score, mIoU, FWIoU, mPA and OA reaching 72.53 %, 78.41 %, 99.86 %, 83.33 % and 99.93 % respectively. Moreover, our model exhibits lower complexity while demonstrating improved capability in detecting landslides with complex shapes and different sizes.

Climate change in Europe and international portfolio allocation: Micro‐level evidence from global funds

AbstractThis paper investigates the impact of climate change on international portfolio allocations of global funds. We select the heat wave disasters in Europe in 2018 as a quasi‐natural experiment and employ the DID framework. Our findings indicate that global funds would reduce their holdings in the affected country after heat wave disasters. The congestion of inland waterways and electricity shortages during the heatwave have resulted in production delays, thereby transmit risks to the financial sector. Countries with higher foreign exposure experience a larger scale of capital outflow after heat waves; while countries with great institutional quality and resilience demonstrate greater capacity to withstand heat wave disasters. The funds with lower risk tolerance are more sensitive to climate change. Additionally, domestic funds will remain in their home countries post‐heatwave when foreign capitals flow away. These findings have important policy implications, and countries with high climate risks should carefully monitor the capital flows. In order to reduce the impact of climate risks, it is crucial to improve the quality of institution and efficiency of government as well as to implement effective disaster prevention and mitigation measures.

Towards inclusive green growth: a holistic analysis of sustainable development goals in the agritourism sector of Jambi Province

This research aims to measure the extent of inclusive green growth in Jambi Province by considering the components of the Inclusive Green Growth Index that contribute to the potential of agrotourism and sustainable growth. It seeks to identify and analyze tourism potentials that can be leveraged to support inclusive green growth in various districts of Jambi Province. Additionally, the study aims to formulate strategies applicable to tourism villages in Jambi Province to realize agrotourism areas focused on improving the well-being of communities and the environment. This research employs both quantitative and descriptive qualitative methodologies. Data sources include primary and secondary data collected through interviews, observations, literature studies, and documentation. Informants were selected using purposive sampling, covering three regencies in Jambi Province: mountainous areas in Merangin Regency, non-mountainous and non-marine areas in Muaro Jambi Regency, and marine areas in Tanjung Jabung Timur Regency. The results indicate that Jambi Province has not yet achieved green inclusivity, with an Inclusive Green Growth Index value of 3.191. The study identifies several sample areas with green development potential, including Rantau Kermas Village in Merangin Regency, Tangkit Baru Village in Muaro Jambi Regency, and Kuala Simbur Village in Tanjung Jabung Timur Regency. Key findings include the green potential of tourism and plantations, dance arts, micro-hydropower plants (PLTMH), electricity, awards, funding, fishermen, locations, culinary, mangrove forests, customary forests, and marine products. Strategies to realize agrotourism areas based on improving community well-being and the environment include strengthening organizations, enhancing the quality of human resources, developing infrastructure, funding programs, applying customary law sustainability, offering tour packages, forming customary forest management groups, conducting research and development, implementing disaster mitigation measures, promoting tourism, and initiating the adopt-a-tree program.

Possibility of Suppressing Fire Spread in the Event of a Large Earthquake by Greening and Demolishing Vacant Houses

In recent years, disaster mitigation measures by greening and demolition of vacant houses to prevent large post-earthquake fire spread have been promoted. However, few studies evaluate its effects on reducing property damage and human casualties, especially in vulnerable areas for earthquakes, such as densely built-up wooden residential areas. In this paper, we develop a model to describe the delay of post-earthquake fire spread between neighboring buildings, and incorporate it into the simulation model. Using the integrated model, we evaluate the reduction of the number of burnt-down buildings and human casualties in densely built-up wooden residential areas, and demonstrate the effectiveness of greening and demolition of vacant houses.

Analysis of bed changes in the segment of the Tien river flowing through Tan Chau

The segment of the Tien River flowing through Tan Chau town is a meandering section with complex flow patterns, influenced by the flow dynamics and the lack of upstream sediment supply. This has resulted in the formation of deep erosional channels that affect the bank stability. This study focuses on evaluating the bed change of the Tien River within Tan Chau town through the analysis of measurement data and some scenarios from numerical modeling. The findings reveal that the Tan Chau - Hong Ngu curved section experiences severe channel erosion, particularly concentrated in the topographic channel and inclined towards the concave bank of Tan Chau (the inner bank). An analysis of causative factors indicates that reduced sediment supply due to dam construction and sand mining activities have led to changes in the riverbed, deeper erosion, and bank erosion near the sand mining area. The results quantifies the sediment deficit in the area at 0.86%, while the impact of sand mining in this area is 0.26%. The findings from this research provide a database to support local planning for bank protection projects and disaster mitigation measures due to bank erosion.

Extraction and analysis of the sea ice parameter dataset of the Bohai Sea from 2011 to 2021 based on GOCI

The Bohai Sea and its surrounding areas are rich in oil and natural gas and play an important role in industry, agriculture and the economy. However, the Bohai Sea suffers severely from sea ice in the winter. While previous research has predominantly focused on methods for retrieving sea ice parameters in the Bohai Sea, analyses of their long-term statistical patterns have been limited. The Geostationary Ocean Color Imager (GOCI) is the first geostationary satellite for ocean color remote sensing, offering high spatial and temporal resolution, which greatly facilitates the extraction of Bohai Sea ice parameters. Utilizing GOCI data, we systematically extracted relevant sea ice parameters for the Bohai Sea region from 2011 to 2021. These parameters include sea ice concentration, sea ice thickness, and sea ice drift. We conducted a comprehensive statistical analysis of the long-term sea ice changes in the Bohai Sea and found that the development process of winter sea ice area is different from the sea ice thickness, and the direction of sea ice drift is basically unchanged. Then we developed statistical models linking sea ice parameters with ocean dynamic factors such as temperature, wind, and drift currents. Among them, the correlation coefficient between the predicted value and the measured value of the sea ice area model is the highest, reaching 0.8382. Furthermore, we examined the previously unexplored relationship between daily sea ice area, sea ice thickness, and accumulated temperature with their respective starting temperatures and accumulation periods. This study provides critical data to support Bohai Sea ice monitoring and marine environmental research. The results of this study contribute to a better understanding of sea ice change trends in the Bohai Sea and inform the development of disaster prevention and mitigation measures.

Research on internal explosion loads in folded arch tunnels: A theoretical approach

To elucidate the loading characteristics in the folded arch tunnel subjected to internal explosion, a field blast test was conducted in a large-scale (1:5) model constructed according to the immersed tube tunnel of Hong Kong-Zhuhai-Macao Bridge. The spatial distribution and time histories of the overpressure around the detonation point were recorded in the folded arch tunnel. The test data indicate that the internal blast loads in the folded arch tunnel is mainly attributed to the shock overpressure and gas overpressure. A fine FE model was developed in the LSDYNA platform, which was validated by the loading test data. The propagation process of blast waves and detonation products along the folded arch tunnel were studied by the developed model, which also helped reveal the interaction mechanism with the tunnel structure. Three existing theoretical models in predicting the internal blast loads were compared and assessed. It is found that the existing theoretical models developed for the internal blast loads has limitations in predicting the blast load in the tunnel, which especially would introduce a large error in manifesting the gas overpressure. A new loading model that enables precisely predicting the internal blast loads in the folded arch tunnel was proposed, which offers valuable insights for the blast-resistant design and disaster mitigation measures for the tunnel structure.

Research on the determinants of intentions and actions toward residential disaster mitigation measures by residents of Important Preservation District for Groups of Historic Buildings

Research on the determinants of intentions and actions toward residential disaster mitigation measures by residents of Important Preservation District for Groups of Historic Buildings

Fragility Analysis and Resilience Assessment of the Single-Column Pier Steel-Concrete Composite Bridge Subjected to Seismic Loads

Abstract With the advantages of a small footprint, wide under-bridge view, and beautiful appearance, single-column pier bridges are widely used in urban bridge networks. However, single-column pier bridges are prone to damage during earthquakes or heavy vehicle use, which can seriously affect normal operations and postdisaster recoveries. Therefore, there is an urgent need to carry out seismic resilience assessments of single-column pier bridges and formulate disaster prevention and mitigation measures from the aspects of design, maintenance, and postearthquake recovery. This paper first establishes a resilience assessment framework for the single-column pier bridge and optimizes a functionality recovery model after an earthquake. Then, a numerical model of a sample bridge is built for resilience fragility analysis. Nonlinear dynamic time history analysis is performed to build a probabilistic seismic demand model, and moment–curvature analysis is performed to build a probabilistic seismic capacity model. Finally, a seismic resilience assessment of the single-column pier bridge is obtained based on the seismic fragility, and a sensitivity analysis is carried out for the pier height, pier section dimension, span and vehicle load level to improve the resilience of the single-column pier bridge.

The Probability of Ship Collision during the Fully Submerged Towing Process of Floating Offshore Wind Turbines

As global warming intensifies, the development of offshore wind farms is swiftly progressing, especially deep-water Floating Offshore Wind Turbines (FOWTs) capable of energy capture in deep-sea regions, which have emerged as a focal point of both academic and industrial interest. Although numerous researchers have conducted comprehensive and multifaceted studies on various components of wind turbines, less attention has been paid to the operational stage responses of FOWTs to wind, waves, and currents and the reliability of their structural components. This study primarily employs a theoretical analysis to establish mathematical models under a series of reasonable assumptions, examining the possibility of collisions between FOWT transport fleets and other vessels in the passage area during the towing process. Using the model, this paper takes the Wanning Floating Offshore Wind Farm (FOWF) project, which is scheduled to be deployed in the South China Sea, as its research object and calculates the probability of collisions between FOWTs and other vessels in three months from the pier near Wanning, Hainan, to a predetermined position 22 km away. The findings of the analysis indicate that the mathematical model developed in this study integrates the quantities and velocities of navigational vessels within the target maritime area as well as the speeds, routes, and schedules of the FOWT transport fleet. By employing statistical techniques and geometric calculations, the model can determine the frequency of collisions between various types of vessels and the FOWT transport fleet during the transportation period. This has substantial relevance for future risk assessments and disaster prevention and mitigation measures in the context of FOWT transportation.

OVERVIEW OF UNDERSTANDING AND PREPAREDNESS FOR EARTHQUAKES IN THE PERSPECTIVE OF VOCATIONAL HIGH SCHOOL STUDENTS

Knowledge of disaster mitigation is the most essential component and a key factor for preparedness. The possessed knowledge typically influences attitudes and concerns, fostering readiness to anticipate disasters. Vocational High School students should be informed about the various disasters that frequently occur in their areas, as well as the procedures to face sudden disasters. The significant loss of lives and various damages to buildings and facilities in the vicinity underscore the need for a deeper examination of mitigation efforts. The objective of this study is to assess the level of understanding and preparedness of Vocational High School students regarding earthquake natural disasters. The research method employed is quantitative, with descriptive statistics as the analytical technique. The instruments used include test instruments and non-test instruments utilizing Google Forms to collect data from several Vocational High Schools in various cities in DKI Jakarta, Sukabumi, and Tangerang. The research findings reveal that 42% of students are unaware of earthquake disaster mitigation measures. Additionally, 69% of students lack knowledge about minimizing damage from earthquakes in terms of building construction. Furthermore, 65% of students are unfamiliar with images related to earthquake-resistant construction. Moreover, 52% of students still do not know the local earthquake resilience features of earthquake-resistant houses. Lastly, 52% exhibit a panicky attitude, hastily evacuating buildings during an earthquake. The conclusion drawn from this research is that the knowledge of Vocational High School students regarding earthquake disasters and their mitigation measures is still low.