Disaster Emergency Management Research Articles

DEVELOPING A LOCALIZED OPTIMAL FLOOD BARRIER IN THE PHILIPPINES

In the Philippines, flood is a usual experience due to its geographical location near the equator. This calls for governmental units to establish flood control protocols that utilize equipment to effectively mitigate the impact of the floods. However, the existing protocols lack proper equipment integrated in their flood protocols that effectively handle flood occurrences. This research aims to improvise the current practices of the Philippine local government units in combating flood by proposing the optimal flood barrier design to be deployed for flood control and damage mitigation and investigate the optimal flood barrier for deployment. The methodology involves revisiting operational manuals of the target community of the Philippine governmental units and exploring existing flood barrier designs in literature and the market, whether in or out of the Philippines. Barriers designed in the literature and market were investigated, where there is a physical experiment conducted for the optimal design using physics concepts and past tests performed by studies. Results demonstrated the amount of force that can be resisted by the barriers, the amount of flood water until it floats, and the maximum velocity until barriers move. This is the first study to investigate the designs of flood barriers that are suitable for deployment and selects the optimal barrier for flood control for the Philippine setting while integrating it to the Philippine flood protocols. This research will be valuable to studies in regards with flood emergency disaster management planning.

A new perspective to understand public response to the Typhoon Doksuri from coastal and inland regions

Massive amounts of data from social media possess the potential to rapidly identify the primary issues of concern in emergency disaster management. In summer 2023, Super Typhoon Doksuri which was an exceptionally special typhoon disaster that caused severe damage to China's coastal areas and disastrous impacts in inland regions, particularly triggered the most severe rainstorm in Beijing area in over a century. To enhance typhoon hazard reduction in both coastal and interior locations, it is crucial to examine public response to these events. This study uses microblog text data from July 27 to August 3 of 2023 to map the public response to Typhoon Doksuri. The Support Vector Machine (SVM) algorithm was used to classify the microblog text in combination with the typhoon path to analyze the spatial and temporal variations of the emotions of the affected individuals. The relationship between changes in public opinion, the distribution of topics, and the major disasters triggered by the residual circulation of Typhoon Doksuri in the Beijing-Tianjin-Hebei region is discussed. The Mentougou mega-storm in Beijing area that occurred in July 2023 is a typical case. The findings demonstrate that during the typhoon event, the focus of public attention changed with the movement of the typhoon path, and various public opinion topics exhibited temporal synchronization. Public sentiment indicates that the overall supportive sentiment is higher than is fearful sentiment. Based on this, it is crucial to strengthen the Beijing-Tianjin-Hebei cooperative emergency response, and response measures were proposed related to urban flood control and drainage construction, public awareness, backward areas, secondary disasters, resident relocation, and social media technology.

Governance strategies and tools towards the improvement of emergency management of natural disasters in transboundary areas

Cross-border emergency management is a pressing issue, especially in contexts where economic, social, infrastructural and natural interdependencies ignore political borders. Different legislative, administrative and organisational barriers can hinder the homogeneity, coordination and effectiveness of any emergency response to a common natural hazard. The GESTI.S.CO. project (Italian acronym for "Management of emergencies and disasters without borders"), co-funded under Grant Agreement No. 475062 of the Italy-Switzerland Interreg Cooperation Programme, has been designed to study and address this issue in the highly interconnected and densely populated border area between the Cantons of Ticino (Switzerland) and Lombardy (Italy). The main objective is to strengthen cross-border cooperation in the management of natural disasters through common solutions for the preparedness of local administrations on both sides of the border, in order to increase cooperation, coordination, integration and mutual assistance in case of need. The GESTI.S.CO. governance approach has produced many results: some of them have been included in the official procedures and tools of the institutions in charge of emergency planning and management in both countries; others, more informal, have helped to share knowledge and know-how and to improve the cooperation and response of stakeholders and local communities in the event of natural disasters. Some of these products have already been positively validated during some hydrogeological and wildfire events that occurred in the study area in 2021 and 2022. Such an approach may be useful for other transboundary areas where some results may be replicable under selected conditions.

Disaster Management and Emergency Response: Improving Coordination and Preparedness

Disasters pose significant challenges to communities worldwide, necessitating effective disaster management and emergency response systems. This study aims to evaluate current practices in disaster management and emergency response, focusing on enhancing coordination and preparedness. Through qualitative analysis, including literature review and library research, this study assesses existing strategies and identifies areas for improvement. The findings underscore the importance of robust coordination mechanisms among various stakeholders involved in disaster management, including government agencies, non-governmental organizations, and community groups. Moreover, the study highlights the critical role of preparedness measures in mitigating the impact of disasters and facilitating timely and effective response efforts. By synthesizing insights from existing literature and case studies, this research provides valuable recommendations for enhancing disaster management and emergency response frameworks. The results emphasize the need for comprehensive planning, capacity-building initiatives, and the integration of technology to strengthen resilience and response capabilities. Furthermore, the study underscores the significance of community engagement and public awareness campaigns in fostering a culture of preparedness and resilience. Overall, this research contributes to the ongoing discourse on disaster risk reduction and emergency management by offering insights into improving coordination and preparedness strategies in the face of natural and man-made disasters.

A multicriteria decision model to improve emergency preparedness: Locating-allocating urban shelters against floods

The increasing prominence of natural disasters in recent years has made emergency disaster management one of the main challenges for building resilient societies. This way, the warming combination with human-induced urban interventions with climate change reshapes the strategic decision-making that public managers must deal with to promote safety and preparedness. Consequently, it implies complex situations under uncertainty that comprise conflicting dilemmas about which decision-makers (DMs) should establish trade-offs. Given this backdrop, this work proposes a risk-based multidimensional model for assessing urban shelter location against flood risk with Decision Analysis and Multi-Attribute Utility Theory. By using principles of the Queue Theory, the decision model undertakes four criteria that measure in a probabilistic manner the alternatives’ performance when considering urban flood disaster evacuation routes in affected areas. Altogether, it enables the DM to establish his/her preferences with views to rank potential locations for mounting temporary shelters and for planning emergency preparedness in risky areas. Being replicable to any urban context, our proposal has the potential to support and promote the development and implementation of crisis protocols consisting of measures to reduce flood impacts and adapt critical areas to climate change. From a numerical application of the proposed model, the DM is encouraged to explore graphical and tabular visualization tools, as well as sensitivity analysis, to establish in strategic terms how to design and implement emergency shelters to reduce flood risks in urban areas effectively.

Dempster–Shafer theory-based information fusion for natural disaster emergency management: A systematic literature review

The frequency and unpredictability of natural disasters pose serious challenges to emergency management in modern society. Effective emergency management requires not only rapid response, but also accurate assessment of the situation, rational allocation of resources and scientific decision-making. Dempster–Shafer theory (DST), as a powerful information fusion tool, has been widely used in natural disaster emergency management in recent years. This study sorted out the core related articles of DST in various directions in the field of natural disaster emergency management, and formed a systematic literature review. In order to support and guide the completion of this work, keywords were selected according to the rules of Systematic literature review (SLR) and the requirements of article content research to screen and determine the literatures. On this basis, relevant information of the selected literatures was analyzed, including authors, institutions, countries, keywords, etc. Then, according to the theoretical framework of integrated emergency management, fifteen structured research questions are put forward, involving various aspects of integrated emergency management system, and these questions are answered in detail. After that, it discussed the literature, and summarized the contribution and future development direction of DST based on information fusion in natural disaster emergency management. The final results show that in the field of natural disaster emergency management, DST plays various and important roles, among which one of the most important roles is the integration of decision-making evidence at various stages of disasters, so as to make better decisions. By combining with other methods, DST improves its limitations. And in the process to expand their scope of use. Then, it focuses on how to solve the extended theory, practical application dimension and related defects of DST in the field of natural disaster emergency management.

Investigating the Intense Sediment Load by Dam‐Break Floods Using a Meshless Two‐Phase Mathematical Model

AbstractExtreme precipitation is increasing the risk of dam breaks and formation occurring debris dams. Accurate prediction of dam‐break wave propagation is critical to disaster emergency management. Intense bed‐load transport by dam‐break floods can result in a dramatic change of topography, which in turn may affect flood propagation. However, only a very few studies have investigated the thin intense bed‐load layer under dam‐break floods. In this paper, a meshless two‐phase mathematical model is utilized to examine the water velocity, sediment velocity and volumetric fraction, and bed‐load transport flux as well as energy dissipation in bed‐load layer. The model is applied to simulate two‐ and three‐dimensional laboratory experiments of dam‐break wave over erodible beds. For the two‐dimensional experiment, the relative root mean square errors in computed water surface are all below 3.60% and those in profiles of bed‐load layer and static bed are mostly below 13.40%. For the three‐dimensional case, the relative error in computed highest water level is lower than 5.9%. Sediment stream‐wise velocity in bed‐load layer follows a power‐law vertical distribution while sediment volumetric fraction decreases linearly upwards. Accordingly, a formulation of the vertical distribution of bed‐load transport flux, contradictory to the parabolic law in existing studies, is proposed. Most of the water mechanical energy transferred to the sediment is dissipated due to the shear stress in the intense bed‐load layer while only a limit part is kept by the sediment grains. Energy dissipation due to sediment shear stress dominates the consumption of total mechanical energy in the two‐phase system.

Experimental study on the impact of the second dam break heights on the evolution of two-dam failure floods

Dam-break floods, especially cascade dam-break floods, could be catastrophic and warranted further investigation to enhance understanding. This paper systematically investigated the impact of break heights of the second dam on the evolution of two-dam failure floods, comparing it with single-dam outburst floods. The experiments were carried out in an inclined rectangular flume with LiDAR technology to capture the free surface. Results indicated that a computational model for the moving hydraulic jump was developed, showing good agreement with experimental results with a relative error of about 10%. The wave height of dam-break flood increased with the increase of evolution distance. The wave front celerity (for dam spacing: L/H = 26) after the flood passed the second dam increased with the break heights. The peak discharges at the second dam site and the peak flow depth (for longitudinal coordinate: x/H = 59) both showed a linear relationship with the initial flow depth in reservoir and the break heights. An increase in the initial flow depth in reservoir or the break heights led to an increase in peak discharges and peak flow depth. This study offered constructive guidance for the risk assessment of multi-dam failure floods and disaster emergency management.

DISASTER EMERGENCY TRAINING TO INCREASE MIGRANT CAPACITY IN SIDOARJO

Migrants seeking asylum in Indonesia are a vulnerable group who need attention and training regarding disaster emergencies. This is because Indonesia is a maritime country which geographically and geologically allows natural disasters to occur. Although aid supplies are very important in emergency situations, preventive measures and preparedness are also equally important so it is necessary to provide health services in the form of expertise in disaster emergencies for migrants. Disaster emergency management efforts are a system that cannot be divided and the quality of life of patients after a disaster injury depends on pre-hospital stage treatment. The aim of this activity is to increase understanding and empowerment by provide outreach and training for migrants living in Sidoarjo. Before counseling, a 10 minutes pre-test was conducted for the participants. followed by a counseling session, training and discussion session for approximately 60 minutes, and after that a post-test was carried out for 10 minutes. Next, the results of the pre-test and post-test are assessed and data processing and evaluation are carried out. The results of the Paired T-tests show a p-value of 0.00 so the sig value is <0.05 which indicates there is a significant difference regarding the pre-test and post-test data. This can be interpreted as an increase in insight, understanding, empowerment, as well as a change in attitude towards migrants after attending the counseling session. Community service activities regarding disaster emergencies for migrants living in Sidoarjo have had a significant impact in the form of increasing insight and empowerment regarding the topic of disaster emergencies.

Evaluation and Spatial–Temporal Pattern Evolution of Synergy Degree of Emergency Management for Urban Flood Disasters from the Perspective of Sustainable Development—The Case of Henan, China

The management of urban flood disasters is a systematic engineering project that requires a great amount of manpower, material resources, and financial resources, and the interaction and coordination degrees of various elements in the system deeply affect the efficiency of the final governance. According to the theories of synergy, composite systems, and sustainable development, this research first established an evaluation index system to determine the synergy degree of urban flood disaster emergency management from the four dimensions of prevention and preparation, monitoring and early warning, response and rescue, and recovery and reconstruction. Then, the synergy degree was explored by using the developed composite system synergy degree model on the basis of the panel data of 18 prefecture-level cities in Henan Province from 2013 to 2021, and synergy level change characteristics were analyzed from the perspectives of time and space. Finally, the obstacle degree model was applied to explore the obstacle factors affecting synergy degree development. The results showed that the overall level of the urban flood disaster emergency management coordination degree in Henan Province was relatively low, and there were significant differences in synergy among cities. Among them, 12 cities presented mild synergy, and 6 cities showed mild nonsynergy. The spatial correlation of the synergy degree was not stable, which revealed a lack of mature coordination mechanisms for flood disaster emergency management among cities. The analysis of obstacle factors showed that recovery and reconstruction subsystems were the main obstacle systems that affected the synergy degree.

The Performance of Landsat-8 and Landsat-9 Data for Water Body Extraction Based on Various Water Indices: A Comparative Analysis

The rapid and accurate extraction of water information from satellite imagery has been a crucial topic in remote sensing applications and has important value in water resources management, water environment monitoring, and disaster emergency management. Although the OLI-2 sensor onboard Landsat-9 is similar to the well-known OLI onboard Landsat-8, there were significant differences in the average absolute percentage change in the bands for water detection. Additionally, the performance of Landsat-9 in water body extraction is yet to be fully understood. Therefore, it is crucial to conduct comparative studies to evaluate the water extraction performance of Landsat-9 with Landsat-8. In this study, we analyze the performance of simultaneous Landsat-8 and Landsat-9 data for water body extraction based on eight common water indices (Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI), Augmented Normalized Difference Water Index (ANDWI), Water Index 2015 (WI2015), tasseled cap wetness index (TCW), Automated Water Extraction Index for scenes with shadows (AWEIsh) and without shadows (AWEInsh) and Multi-Band Water Index (MBWI)) to extract water bodies in seven study sites worldwide. The Otsu algorithm is utilized to automatically determine the optimal segmentation threshold for water body extraction. The results showed that (1) Landsat-9 satellite data can be used for water body extraction effectively, with results consistent with those from Landsat-8. The eight selected water indices in this study are applicable to both Landsat-8 and Landsat-9 satellites. (2) The NDWI index shows a larger variability in accuracy compared to other indices when used on Landsat-8 and Landsat-9 imagery. Therefore, additional caution should be exercised when using the NDWI for water body analysis with both Landsat-8 and Landsat-9 satellites simultaneously. (3) For Landsat-8 and Landsat-9 imagery, ratio-based water indices tend to have more omission errors, while difference-based indices are more prone to commission errors. Overall, ratio-based indices exhibit greater variability in overall accuracy, whereas difference-based indices demonstrate lower sensitivity to variations in the study area, showing smaller overall accuracy fluctuations and higher robustness. This study can provide necessary references for the selection of water indices based on the newest Landsat-9 data. The results are crucial for guiding the combined use of Landsat-8 and Landsat-9 for global surface water mapping and understanding its long-term changes.

Examining organizational collaboration and resource flows of disaster response system based on a time-dynamic perspective

Increasing the efficiency of organizational collaboration and resource flows is key to improving the emergency response performance. Given that previous studies did not consider the interactions and dynamic characteristics of emergency response organizations and resources, this study divided the emergency response into four stages and analyzed the relationship between organizational collaboration and resource flows by combining the network attributes of emergency response goals at each stage. The 2022 Luding earthquake was selected as a case study, and a multisource mixed data method was used to identify 381 organizations and 2496 organizational relationships. Using the social network analysis, the dynamic evolution characteristics of the emergency response networks (ERNs) and organization-resource two-mode networks were analyzed. The results showed that the ERNs generally exhibited the following trends: a more compact structure, balanced distribution, evolution from decentralization to centralization, and homogenous organizational collaboration. A correlation existed between changes in the organizational status and ERN attributes, with government organizations always at the core and non-profit organizations gradually rising. The evolution of the resources was closely related to the network attributes and organizational relationships. We identified the strengths of China's current emergency management system, such as enhanced performance, improved information infrastructure, and emphasis on the engagement of the military and social organizations. We recommend the following for future practice: enhancing the information technology system, establishing a mechanism for the participation of social forces, and strengthening the management of emergency stockpiles. These will help improve the disaster emergency management performance and reduce casualties and losses.

A cross-view intelligent person search method based on multi-feature constraints

ABSTRACT Person searches aim to simultaneously locate and identify persons to be queried from different scenes, which is crucial for disaster emergency management and public safety. However, the high variability of environmental features in different video scenes, along with the susceptibility of people searching for occlusions or dense populations, results in existing methods suffering from inefficiency and poor accuracy in searching for cross-view persons. Therefore, we propose a cross-view intelligent person search method based on multifeature constraints. First, we establish the global-local context-aware (GLCA) module, which fully extracts the differential personnel features. Second, we construct the semantic complementarity and feature aggregation (SCFA) module for personnel-scale feature constraints in different contexts. Third, we constrain the method in terms of person spatial, person identity, and detection confidence features to improve person search accuracy. Finally, we construct a case experiment dataset, select two public benchmark datasets, and conduct a detailed experimental analysis based on them. The results show that our method can be applied to personnel search tasks in complex scenarios well, and the search results outperform those of 25 other state-of-the-art algorithms, with mAPs improved by 0.41%−19.71%. This approach effectively enhances the informatization level of disaster emergency rescue and public safety management.

Disaster literacy in disaster emergency response: a national qualitative study among nurses

BackgroundAs the largest group of healthcare professionals, nurses play an indispensable and crucial role in disaster response. The enhancement of nurses’ disaster literacy is imperative for effective disaster emergency management. However, there is currently a lack of knowledge regarding nurses’ disaster literacy. This study represents the first attempt to explore the key components and characteristics of disaster literacy among nurses.MethodsA qualitative descriptive design was employed, and the reporting followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines (refer to File S1). The purposive sampling method was utilized. Thirty-one rescue nurses from 31 medical institutions across 25 provinces and regions in China were recruited to participate in the study. The respondents were requested to share their experiences and insights regarding disaster rescue operations. Inductive content analysis was employed for data examination.ResultsThe results indicated that rescue nurses universally recognized that there was a pressing need to enhance the level of disaster literacy among nurses. The disaster literacy of nurses encompasses nine dimensions: physical and mental quality, disaster rescue general knowledge, professional and technical competence, professional ethics, teamwork, emotional ability, information literacy, leadership, and knowledge transformation.ConclusionsTo ensure national sustainability, government departments, healthcare organizations, and hospital administrators can accurately evaluate the disaster literacy of individual clinical nurses, groups, and the workforce as a whole through nine dimensions, which also can provide evidence to support the development of precision strategies to strengthen the disaster literacy of nurses.

Research on Road Geological Hazard Risk Assessment Model Based on Computational Deep Learning Algorithm Integrated With GIS

This paper studies the geological disaster emergency command and management system based on geographic information system. This system is for the province, city, county land resources and other aspects of the comprehensive application, the realization of real-time information display, meteorological early warning, group measurement and mass prevention, monitoring and early warning, major disaster management, prevention plan, quick report processing, emergency investigation, emergency disposal, emergency consultation and other functions. Through the GSM network, the monitoring data is sent to the monitoring center through the mobile phone, and then the monitoring center processes, stores, displays and alarms the monitoring data. Finally, B/S structure is used to build a remote Web data service publishing platform, so that it can carry out real-time monitoring at any place, and improve the speed, efficiency and intuition of high-speed slope disaster. It is proved that the method has the advantages of stable operation, accurate data, fast transmission speed and high monitoring accuracy through the practical application of a highway project foundation pit slope monitoring.

Earthquake scenario-specific framework for spatial accessibility analysis (SAA) of emergency shelters: a case study in Xichang City, Sichuan Province, China

The spatial accessibility of emergency shelters, indicating the difficulty of evacuation and rescue, is crucial for disaster mitigation and emergency management. To analyze accessibility, an effective approach is to evaluate the service capacity of emergency shelters. Multifaceted factors were employed to enhance the quantitative accuracy of accessibility indicators. However, scenario-specific analysis has not been emphasized. Considering the devastating potential of great earthquake disasters, we cannot ignore the impact of these scenarios on emergency shelter accessibility, especially in areas with high seismic risk. In this study, we developed an earthquake scenario-specific framework for spatial accessibility analysis (SAA), which integrates the service capacity of emergency shelters and the impact of strong ground motion and fault rupturing. We applied this framework to the urban area of Xichang City in Sichuan Province, western China. Xichang City, located in the linked area of the Anninghe fault and Zemuhe fault with many extreme historical earthquake disaster records, is prone to high seismic risk. We firstly collected emergency shelter and road network data in Xichang City. We then applied SAA based on the road network, using the network analysis method. After that, we analyzed the impact of strong ground motion on accessibility and generated the setback zone of fault rupturing. We integrated the effect of strong ground motion on accessibility within the setback zone of active faults. Finally, we generated a comprehensive accessibility map, considering both the predicted strong ground motion and potential fault rupturing. Our results show that the accessibility level changed in several towns of urban Xichang City due to strong ground motion and fault rupturing. The accessibility level decreased in Lizhou, Xingsheng, and Anning Towns. For areas with mapped fault lines, the accessibility level is Very-Low. Our results demonstrate the impact of earthquake damage on the accessibility of emergency shelters and the complexity of evacuation in earthquake scenarios. In general, we added earthquake rupturing and ground motion characteristics into the SAA framework. This framework will help us enhance the reliability of SAA and the feasibility of seismic vulnerability evaluation.

A Deep Parallel Hybrid Fusion Model for disaster tweet classification on Twitter data

Disaster tweet classification has gained significant attention in natural language processing (NLP) due to its potential to aid disaster response and emergency management. The goal of disaster tweet classification is to automate the identification of informative tweets containing information related to various types of disasters, such as floods, earthquakes, wildfires, and more. This classification task plays a crucial role in real-time monitoring, situational awareness, and timely response coordination during emergency situations. In this context, we propose a Deep Parallel Hybrid Fusion Model (DPHFM) that combines features from Convolutional Neural Networks (CNNs) and Bidirectional Long Short-Term Memory (Bi-LSTM) as base learners. The features extracted from these base learners are combined using a fusion mechanism and then reconstructed for input to a meta-learner for making predictions. The DPHFM is trained on disaster datasets, such as crisisMMD, which consists of seven natural disaster events. The model underwent thorough evaluation using various metrics, demonstrating an average performance improvement of 90% to 96%. Furthermore, the proposed model’s performance surpassed that of other state-of-the-art models, showcasing its potential for disaster tweet classification using deep learning techniques.

Automatic Extraction Method of Landslide Based on Digital Elevation Model and Digital Orthophoto Map Data Combined in Complex Terrain

This study aims to accurately determine the distribution of landslides in the complex terrain of Jiangdingya, Nanyu Township, Zhouqu County, Gansu Province. The digital orthophoto map (DOM) and digital elevation model (DEM) are used to accurately identify landslide areas and analyze associated data. Based on image-based supervised classification, the influence factor constraint analysis is used to further identify and delineate the landslide area. Three mathematical morphology operations—erosion, dilation, and opening—are then applied to automatically identify and extract landslides. Experimental results demonstrate that achieving an accuracy, precision, and recall of 98.02%, 85.24%, and 84.78% shows that it is possible to better avoid interference caused by complex terrain with rich features. High-resolution DEM and DOM data contain rich spectral and texture information. These data can accurately depict geomorphic features of complex terrain and aid in identifying landslide-prone areas when combined with mathematical morphology processing. This contribution is important for identifying landslides in complex terrain and emergency disaster management.

PERAN PEMERINTAH DAERAH DALAM PENGURANGAN RISIKO BENCANA MELALUI PENINGKATAN KETAHANAN BENCANA DAERAH DI KABUPATEN TANAH BUMBU

Exploitation of natural resources triggers a decrease in the carrying capacity and capacity of the environment and results in climate change and various kinds of disasters. The objectives of this research are Analyzing the role of the Regional Government in implementing the Regional Resilience Index Improvement Program; Analyzing the inhibiting factors of the Regional Resilience Index improvement that has been carried out by the Tanah Bumbu Regency Government; Determining the priority scale of the Regional Disaster Resilience Improvement Program. Data analysis used in this study is Calculating the percentage of indicator achievement based on the Technical Guidelines for the Regional Resilience Index Assessment Tool, Descriptive analysis of inhibiting factors in increasing the Regional Disaster Resilience Index (71 Indicators) to stakeholders through interviews, Creating a priority scale matrix to determine recommendations. Determination of the priority scale matrix is based on Minimum Service Standards and ranking of relevant stakeholders. The results of research on the role and inhibiting factors of the Tanah Bumbu district government in increasing the Regional Resilience Index are Indicators implemented in the priority of Strengthening Policies and Institutions by 60.00%. Indicators implemented in the priority of Risk Assessment and Integrated Planning amounted to 75.00%. Indicators implemented in the Information System Development, Training and Logistics priority by 69.23%. Indicators implemented in the priority of Thematic Handling of Disaster Prone Areas amounted to 80.00%. Indicators implemented in the priority of Increasing the Effectiveness of Disaster Prevention and Mitigation by 70.00%. Indicators implemented in the priority of Strengthening Disaster Preparedness and Emergency Management by 55.00%. Indicators implemented in the Disaster Recovery System Development priority of 75.00%.

Seismic landslide susceptibility assessment using principal component analysis and support vector machine

Seismic landslides are dangerous natural hazards that can cause immense damage to human lives and property. Susceptibility assessment of earthquake-triggered landslides provides the scientific basis and theoretical foundation for disaster emergency management in engineering projects. However, landslide susceptibility assessment requires a massive amount of historical landslide data. Evidence of past landslide activities may be lost due to changes in geographical conditions and human factors over time. The lack of landslide data poses difficulties in assessing landslide susceptibility. The aim of this study is to establish a generalized seismic landslide susceptibility assessment model for applying it to the Dayong highway in the Chenghai area, where earthquakes occur frequently but with a lack of landslide data. The landslide data used comes from the 2014 Ludian Ms (Surface wave magnitude) 6.5 earthquake in a region with geographical conditions similar to those in the Chenghai area. The influencing factors considered include elevation, slope, slope aspect, distance to streams, distance to faults, geology, terrain wetness index, normalized difference vegetation index, epicenter distance and peak ground acceleration. The frequency ratio method is used to eliminate influencing factors with poor statistical dispersion of landslides. Principal component analysis (PCA) is utilized to reduce the dimensionality of landslide conditioning factors and to improve the transferability of the assessment model to different regions. A support vector machine model is used to establish the susceptibility assessment model. The results show that the accuracy of the PCA–SVM model reaches 93.6%. The landslide susceptibility of the Chenghai area is classified into 5 classes, with the “Very high” landslide susceptibility class accounting for 0.63%. The 13-km section in the middle of the Dayong highway, which accounts for 8.9%, is identified as the high-risk area most obviously impacted by seismic landslides. This study provides a new approach for seismic landslide susceptibility assessment in areas lacking in landslide inventory data.