Local Disaster Research Articles

The Level of Disaster Awareness and Preparedness of San Jose Vegetable Farmers in Monkayo, Davao De Oro: Basis for Extension Intervention

This study investigates the level of disaster awareness and preparedness among the San Jose Vegetable Farmers in Monkayo, Davao de Oro, a region frequently impacted by natural disasters due to its geographical and climatic conditions. The primary aim is to assess the demographic profile, disaster awareness, and preparedness levels of these farmers. Using a descriptive quantitative research design, data were collected through surveys involving 50 participants selected via purposive sampling. The results reveal a diverse age group with half of the respondents aged 41 years or older. Most farmers have occupied their land for over 31 years, with the majority operating on small-scale land holdings of 1-2 hectares. The findings indicate a high level of disaster awareness among the farmers, characterized by a strong understanding of disaster risks and active engagement in education and training activities. However, there is a slight gap in their confidence in securing themselves and their families. In terms of preparedness, the farmers exhibit robust readiness, particularly in family communication and community plans. Nonetheless, areas such as disaster supplies, and first aid training require further enhancement. The involvement of government and local disaster management offices has been crucial in supporting and strengthening the community’s preparedness efforts, ensuring a resilient approach to disaster management. This study underscores the importance of continuous education, resource allocation, and community involvement in enhancing disaster resilience among small-scale farmers in disaster-prone areas. Extension services, provided by agricultural and disaster management experts, can play a crucial role in addressing the identified gaps and strengthening the community’s overall awareness and preparedness.

Politics versus Preparedness? How Electoral Incentives Affect the Provision of Local Disaster Public Goods in the Philippines

Abstract There is an expectation that elections create responsive policymakers that provide optimal public services. However, does this hold true when it comes to non- particularistic and non-immediate goods like disaster preparedness projects? In this exploratory study, I argue that electoral incentives can discourage the provision of local disaster public goods due to their non-particularistic and non-immediate nature. Using datasets containing electoral data and government ratings of local disaster public goods in Philippine cities and municipalities from 2017 to 2021, I find evidence that local disaster public goods provision is affected by (1) the intensity of local electoral competition and (2) the timing of the elections. Estimates suggest that local disaster public goods decline in quality one year before elections. Furthermore, in municipalities, more intense electoral competition is linked to lower quality provision of these collective goods. The findings illustrate how electoral incentives distort leaders’ policymaking against their constituencies’ long-term, common needs.

PKM Sosialisasi Tanggap Bencana dan Pengelolaan Berkelanjutan dalam Upaya Menjaga Wisata Alam di Desa Gosari

Gosari Amusing Park (Wagos) is a natural tourism destination located in Gosari Village, Gresik Regency, Indonesia. This community-based research explores an approach that focuses on two crucial aspects: disaster preparedness and sustainable management in the context of village tourism. The primary objectives are to enhance awareness of natural disaster potentials in Wagos while preserving its existence and sustainability as a local entrepreneurship venture.Participatory action research is adopted in three stages in this mentoring program: preparation, implementation, and evaluation. The engagement team, comprising academics, students, and the East Java Regional Disaster Management Agency (BPBD), collaborates with local youth. They work alongside the head of Gosari Village to identify risk mitigation measures, including the installation of evacuation route signs.During the implementation stage, the activities include disaster awareness campaigns, Focus Group Discussions (FGD) to identify vulnerable points, and the introduction of INARISK software along with evacuation simulations for the youth managing Wagos and the Toppi community.The evaluation stage emphasizes the importance of re-socialization by the youth to the local community, the installation of permanent evacuation signs, and impromptu simulations at tourist locations. The results show that the success of disaster risk mitigation heavily depends on community awareness and local entrepreneurship. Wagos, as a tourist village, has proven its existence through the creation of social values and effective promotional efforts. In conclusion, disaster awareness and sustainable management are crucial to maintaining tourist villages in the face of natural disasters and increasing business competition. This community-based research also asserts that an interdisciplinary approach and understanding the local disaster cycle are key to addressing these challenges.

A REVIEW OF STOCK MARKET IMPACT OF ENVIRONMENTAL CATACLYSMS AND LESSONS FOR INVESTORS

The objective of this paper is to present a review analysis of stock market impact of environmental disaster with the factors that orchestrate the impact, and to offer a novel framework for investors and managers. The paper applied an in-depth empirical review and synthesis method. Findings from the review and synthesis of empirical literature provide strong evidence that environmental disasters have diverse effects on the stock markets with majority of the literature reporting adverse effects on the stock markets. Additionally, findings are more preponderant on short run impact than on long run effects. Findings also show that environmental disasters may offer unique arbitrage opportunities for short-selling investors. The paper concludes by highlighting the capacity of environmental finance as one of the catalysts to bolster corporate adaptive capacity to environmental disaster. Furthermore, the degree of environmental disaster impact on stock market may depend on factors such as the type of environmental disaster, geographical location of environmental disaster, economic sector, stage of economic development, length of disaster and intensity of disaster. Accordingly, the paper develops a framework, which is recommended as a model for further research agenda on environmental disaster effect on stock markets.

A study on the establishment of database for local government disaster response and decision support system in the nuclear accidents

ABSTRACT Radiological disasters have been recognized as a prominent societal catastrophe worldwide since the Fukushima nuclear accident in 2011. In order to cope with such disasters, efforts have been made to improve disaster response plans and systems based on the lessons learned from the Fukushima accident. Particularly, as demonstrated by the Fukushima case, radiological disasters require the assumption of large-scale evacuation of residents. Thus, it is essential for prompt and accurate decision-making to take place at the local government’s Emergency Management Center (EMC), enabling smooth execution of the missions assigned to personnel at the field. This is crucial for protecting the lives of residents and ensuring their safety. However, the existing systems for effective response to radiological disasters are relatively inadequate compared to other types of disasters. To overcome these limitations, this study aims to develop Standard Operating Procedures (SOPs) that are optimized for radiological disaster response by standardizing the Field Measure Motion Manual at nuclear safety for local governments. Based on these SOPs, The Resident Protection Measures Support System (RPMS) will be proposed, which enables the timely dissemination of specific missions and information to personnel, while providing real-time information on the situation at the field to the EMC, supporting decision-making and facilitating effective situation management.

Data-driven evacuation and rescue traffic optimization with rescue contraflow control

In response to local sudden disasters, e.g., high-rise office or residential building fire disasters, road occupation can cause conflicts, and traffic directions may be opposite between evacuation vehicles and rescue vehicles; moreover, lane contraflow can be adopted to meet these surge traffic demands. However, lane contraflow that provides more roads for rescue vehicles reduces the traffic supply in the evacuation direction. It is unclear how to control the number of contraflow roads used by rescue vehicles to coordinate evacuation and rescue traffic operations. Here, we adjust the critical rescue traffic volume of reversing the normal road traffic direction to control rescue contraflow. Additionally, we propose a multiobjective mixed integer linear programming formulation for evacuation and rescue traffic optimization. Additionally, considering that the upper limit of the critical rescue traffic volume is unknown and that the proposed formulation includes multiple objectives and multi-priority vehicle classes, a three-stage solving algorithm is developed. Next, a large-scale evacuation and rescue traffic optimization result dataset is obtained for the Nguyen–Dupuis road network, and the impact of different rescue contraflow control plans on evacuation and rescue traffic is studied based on data-driven statistical analysis. The results show that by adjusting the optimal rescue traffic route, the critical rescue traffic volume for reversing the normal road traffic direction can reduce the interference of rescue traffic to evacuation traffic operation performance without reducing rescue traffic operation performance, and can be used to coordinate evacuation and rescue traffic operation under rescue contraflow.

Implications of trust, preparedness, risk perceptions, and local context on deprivation costs and disaster relief planning

Deprivation Costs Functions (DCFs) are key to designing effective relief distribution operations after disasters. In this paper, data are collected in Colombia and Ecuador to estimate DCFs for water and food, considering the influence of individuals' attitudes on preparedness, risk perception, and trust in response agents. Hybrid Choice Models are used to analyze and compare the estimated DCFs. The analyses confirm that DCFs differ by commodity. Additionally, socioeconomic characteristics of individuals influence their willingness to pay for critical supplies to reduce their own suffering. Preparedness, risk perceptions and trust in response agents impact individuals' behavior in disaster situations. The results also show that community and religious groups are considered the most trusted response agents in both countries. As a result, their involvement in official relief efforts should be more articulated. Colombia and Ecuador show significant differences in their estimated DCFs, confirming that deprivation costs are context-specific by nature. As such, DCFs should not be directly transferred among disaster locations. The findings from this study will support decision-makers in designing effective preparedness and response plans that are based on trust relationships that serve as foundations for community resilience.

Rainfall-Induced Landslide Susceptibility Assessment and the Establishment of Early Warning Techniques at Regional Scale

This study builds upon deterministic evaluations of the extensive cumulative rainfall thresholds associated with shallow landslides in the Gaoping River Basin, with a specific focus on the necessary response times during typhoon and intense rainfall events. Following the significant impact of Typhoon Morakot on the Liugui area, our investigation enhances previous research by employing a downscaled approach. We aim to establish early warning models for village-level, intermediate-scale landslide cumulative rainfall thresholds and to create action thresholds for small-scale, key landslide-prone slopes. Our inquiry not only combines various analytical models but also validates their reliability through comprehensive case studies. Comparative analysis with the empirical values set by the Soil and Water Conservation Bureau (SWCB) and the National Center for Disaster Reduction (NCDR) provides a median response time of 6 h, confirming that our findings are consistent with the response time frameworks established by these institutions, thus validating their effectiveness for typhoon-related landslide alerts. The results not only highlight the reference value of applying downscaled cumulative rainfall thresholds at the village level but also emphasize the significance of the evaluated warning thresholds as viable benchmarks for early warnings in landslide disaster management during Taiwan’s flood and typhoon seasons. This research offers a refined methodological approach to landslide early warning systems and provides scientific support for decision making by local governments and disaster response teams.

Enhanced glacial lake activity threatens numerous communities and infrastructure in the Third Pole

Glacial lake outburst floods (GLOFs) are among the most severe cryospheric hazards in the Third Pole, encompassing the Tibetan Plateau and surrounding Himalayas, Hindu Kush, and Tianshan Mountains. Recent studies on glacial lake changes and GLOF characteristics and risks in this region have shown scattered and insufficiently detailed features. Here, we conduct an appraisal of the GLOF risks by combining high-resolution satellite images, case-by-case high-precision GLOF modeling, and detailed downstream exposure data. The glacial lake changes from 2018 to 2022 in the region were primarily driven by the accelerated expansion of proglacial lakes. The GLOF frequency has exhibited a significant increasing trend since 1980, with intensified activity in Southeastern Tibet and the China-Nepal border area over the past decade. Approximately 6,353 km2 of land could be at risk from potential GLOFs, posing threats to 55,808 buildings, 105 hydropower projects, 194 km2 of farmland, 5,005 km of roads, and 4,038 bridges. This study directly responds to the need for local disaster prevention and mitigation strategies, highlighting the urgent requirement of reducing GLOF threats in the Third Pole and the importance of regional cooperation.

Local Safety Map for a Cornerstone of Local Disaster Prevention: A Case Study of a Historical Local Town in Japan

This paper examines the requirements for creating a local safe map, which is the core of regional disaster prevention, through a case study in a historical local city in Japan. Amid the rising awareness of disaster prevention, efforts are being made in various places to voluntarily create disaster prevention maps through town walks. It is expected to improve residents' awareness of disaster prevention, improve local disaster prevention capabilities, and revitalize local communities. What are the requirements for a local safety map creation to continue to play a central role in regional disaster prevention rather than being a temporary event? Based on our past experiences, we review our research activity what is necessary to make such map-making the core of regional disaster prevention. The following is findings through our experience in the map-making activities. Sustainable development is possible by making it a regular activity in the district rather than a one-off event. Sharing of subjective information in cooperation with the disaster prevention division leads to improve reliability of information by consensus with the members and revitalization of activities through workshops. it is also necessary to select media that provide information from the user's perspective.

Research on landslide susceptibility prediction model based on LSTM-RF-MDBN.

The occurrence of landslide disasters causes huge economic losses and casualties. Although many achievements have been made in predicting the probability of landslide disasters, various factors such as the scale and spatial location of landslide geological disasters should still be fully considered. Further research on how to quantitatively characterize the susceptibility of landslide geological disasters is necessarily important. To this end, taking the Wenchuan earthquake as the research area and extracting eight influencing factors, including terrain information entropy (Ht), lithology, distance from rivers, distance from faults, vegetation coverage (NDVI), distance from roads, peak ground motion acceleration (PGA), and annual rainfall, a landslide susceptibility prediction model was hereby established based on LSTM-RF-MDBN, a landslide susceptibility prediction map was drawn, and the spatial distribution characteristics of landslide disasters were analyzed. The results showed that (1) LSTM had good prediction results for the eight influencing factors, with an average prediction accuracy of 85%; (2) compared with models such as DNN and LR for predicting landslide disaster points, the AUC value of RF for predicting landslide point positions reached 0.88, presenting a higher accuracy compared to other models; (3) the AUC value of the landslide susceptibility prediction model based on LSTM-RF-MDBN reached 0.965, which had a high accuracy in predicting landslide susceptibility. Overall, the research results can provide a scientific basis for selecting the best strategy for landslide disaster warning, prevention, and mitigation.

Peri-urban Community Resilience in Facing the Dynamics of Global Climate-change Impacts toward Sustainable Development

This study analyses the resilience of peri-urban communities in the face of increasingly complex and dynamic global climate change to environmental impact. This study aims to understand the characteristics of peri-urban societies, the factors that influence their resilience, and strategies needed to increase their resilience in the face of climate change. This study uses a qualitative approach with a case study method in Kebalen, Bekasi, and one peri-urban city in Indonesia. Data were collected through in-depth interviews, observations, and document analysis. The results showed that the diverse characteristics of peri-urban communities affect their resilience in the face of climate change. Factors such as resources, accessibility, and social support also affect the resilience levels of peri-urban societies. Strategies needed to increase the resilience of peri-urban communities include collaboration in community empowerment, education, and training in local resource management disasters as well as improving infrastructure and accessibility. This study contributes to the understanding of the role of peri-urban communities in addressing the impacts of global climate change. It produces recommendations for the government, private sector, and community disaster management to synergize and increase the resilience of peri-urban communities.

Satellite constellation method for ground targeting optimized with K-means clustering and genetic algorithm

This study proposed a satellite constellation method to cluster targets using machine learning and achieve the desired revisit performance for each target in an area of interest. Because a typical satellite constellation, such as the Walker method, does not consider the geometrical dynamics between the satellite and Earth's surface target, the target-oriented revisit performance analysis and the application of optimization method are limited. To overcome these limitations, this study developed a satellite constellation method that is customized according to the target using a repeating ground track orbit and machine learning techniques. The proposed model groups aim to maximize satellite revisit performance via K-means clustering and determine the optimal number of satellites required to achieve the desired revisit performance for each target through a quick and accurate accessibility analysis of various target distributions. This study revealed that three to five target clusters are more effective in improving the satellite revisit performance than a typical single target cluster, while identifying that the density of the target distribution is a significant influencing factor. Finally, the proposed model achieved the desired revisit performance, guaranteeing a timely response for 30 major disaster locations in East Asia and validating the model's optimal performance.

Effects of web geographic information system (GIS) technology and curriculum approaches on education for disaster risk reduction

Abstract. Disaster risk reduction education (DRRE) is a strategy to mitigate the harmful effects of disasters. The implementation of DRRE in schools is on the rise, and web geographic information system (GIS) technology in DRRE is becoming increasingly prevalent. However, little knowledge exists about whether students can improve their understanding of disaster risk reduction (DRR) through web GIS technology and which factors affect their learning of web hazard maps. This study has provided materials and curricula for DRR education in Chinese and Japanese high schools and utilized them eight times in the classroom between 2020 and 2022. These classes had three forms of implementation due to the COVID-19 pandemic: online, on-site and online–on-site mixed. The students first answered a pretest. Then they learned about DRR using the explanatory web pages and the web hazard maps by answering quizzes shown on the pages. After that, they answered a posttest and a questionnaire. Most students exhibit improved results after utilizing the digital DRR materials. This improvement is pronounced for the on-site implementations, while the mixed online–on-site implementation proves less effective. The pretest scores for the implementations using local disaster cases are low, but the subsequent improvement is significant. The ability of students to utilize electronic devices affects the learning of GIS-related content rather than other aspects. The daily use of online maps and attention to disaster prevention and mitigation affect the learning of all the materials. Increasing the use of online hazard maps is key to realizing social DRR.

Analysis of Flood-Prone Areas on Bekasi River Watershed

Das Kali Bekasi is an area that has physical conditions that support the occurrence of local and natural flood disasters during the rainy season. This research aims to: (1) Determine the distribution of floodprone areas in the Bekasi River Watershed, (2) Find out the most dominant factors of flood vulnerability that occur in the Bekasi River Watershed. The method used in the research is quantitative descriptive analysis. Analyze the data to determine the distribution area prone to flooding by weighting scoring and overlaying rainfall, land use, slope, soil type, and river density. To find out the dominant factors that cause flood vulnerability, a correlation test is used. The results of the research are (1) Flood vulnerability in the Bekasi river basin, based on the results of this research, is divided into 3 classes, namely the not vulnerable class with an area of 82.61 Km² (5.93%), the moderately vulnerable class with an area of 323.85 Km² (23, 26%), very vulnerable class with an area of 985.96 Km² (70.81%). (2) Correlation test to determine the dominant factor causing flooding in the Bekasi River basin and it is known that the dominant factor is the slope parameter, followed by the river density parameter, soil type parameter, land use parameter, and rainfall parameter with the lowest correlation value.

Post-earthquake recovery and its driving forces of ecological environment quality using remote sensing and GIScience, a case study of 2015 Ms8.1 Nepal earthquake

Natural hazards always have significant impacts on the regional ecological environment, causing huge damages to biodiversity, soil erosion, and impoverishment. This study aimed to analyze the variation of ecological environment quality in Nepal from 2014 to 2018, with a specific focus on the impact and recovery of the 2015 Ms8.1 Nepal earthquake. We utilized Google Earth Engine (GEE) and remote sensing based ecological index (RSEI) to evaluate the ecological environment quality. Moreover, Moran’s I and Geodetector model were employed to explore spatial clustering and driving forces of post-earthquake recovery. The results indicate that after the 2015 Nepal earthquake, there was a decrease of 0.0225 in the mean RSEI in Nepal. The monitoring of the severe-affected areas showed that the regional environmental quality gradually improved within three years after the earthquake. After a span of three years, the ecological environment managed to recover to its pre-earthquake level. In terms of spatial distribution, there is a notable correlation in Nepal, with the ecological environment exhibiting higher quality in the southern regions and lower quality in the northern regions. By examining the driving forces behind the changes in ecological environment quality during the post-earthquake recovery period, it has been determined that altitude, precipitation, and their interaction serve as influential factors. These findings provide valuable insights into the state of ecological environment recovery after the 2015 Nepal earthquake. Furthermore, this study establishes a robust theoretical foundation for local decision-makers to develop ecological protection measures and enhance local disaster risk management.

Nonprofit Disaster Response and Climate Change: Who Responds? Who Plans?

Abstract As weather disasters intensify under the impacts of climate change, an important public policy question is whether the kinds of organizations most likely to provide disaster relief are themselves planning for climate change. A statewide Indiana survey of the leaders of a wide variety of community “social safety net” organizations (N = 467) provides rich descriptive data to understand the realities of local disaster planning as it relates to climate change. Our findings support federal disaster policy in showing first that most of these charities have been or expect to be involved in local disaster relief, either as a primary or secondary mission focus. Charities identifying as primarily disaster responders are much more likely to belong to local emergency planning networks and slightly more likely to plan for emergencies. However, most charity leaders do not acknowledge climate change’s human origins and have not discussed climate change at the board level, with this position strongly related to their understanding of climate change’s potential impact on the communities they serve. And most have not taken some risk mitigation steps. We conclude that the Federal Emergency Management Authority’s national disaster response policy, which relies on the readiness of nonprofits to fill in service roles, does not account for the potential unpreparedness of nonprofits themselves. Policymakers should expand their “whole-community” (three-sector) approach to reinforce local network opportunities as forums for exchanging experience and knowledge, including an explicit linkage between the communication of the science of climate change and emergency planning.

Assessment of Urban Local High-Temperature Disaster Risk and the Spatially Heterogeneous Impacts of Blue-Green Space

Urban high-temperature disasters have gradually emerged as a significant threat to human society. Therefore, it is crucial to assess and identify areas at risk of such disasters and implement urban planning measures aimed at mitigating their impact. Additionally, a multitude of studies have demonstrated the significant cooling effect of urban blue-green spaces (UGBS), which play a pivotal role in urban environments. Incorporating a UBGS layout into planning and evaluation processes has substantial potential for mitigating high-temperature disasters. This paper presents the construction of a set of assessment processes for mitigating urban high-temperature disaster risk using a UBGS structure layout specifically for the main urban area of Harbin, China. We employed GIS and multi-source remote sensing imagery to develop local climate zone (LCZ) maps applicable to the designated study area. The differentiated impact of UBGS factors on high-temperature disaster risk was determined using the multi-scale geographical weighted regression model (MGWR). The results showed the following: (a) There was an overall low risk level, with 19.61% of the high-risk areas concentrated within the second ring road, forming a spatial pattern characterized by “one line, one cluster”. (b) The risk of the building category LCZs was generally higher than that of the natural category LCZs. The risk of the architectural LCZs could be summarized as the risk of low-density LCZs being smaller than that of the high-density LCZs, except LCZ 5. The mean value of the LCZ 2 and LCZ 5 types was the highest. (c) Through indicator screening, AREA_MN, SHAPE_MN, PD, and NP were found to be significant determinants influencing the risk, and the effectiveness and spatial differentiation of these main factors exhibited notable disparities. (d) By comparing different LCZ types, we concluded that the mitigation effect of these factors on risk may be interfered with by building height (BH); NP may be positively interfered with by BH; and PD and SHAPE_MN may be negatively interfered with by BH. The research results provided a new perspective and practical scientific basis for high-temperature disaster risk-mitigation planning based on UBGSs under LCZ classification.

Evaluation of groundwater contamination and associated human health risk in a water-scarce hard rock-dominated region of India: Issues, management measures and policy recommendation

Groundwater is the most precious resource on the earth's surface, providing fresh drinking water for human beings and supplying water for plants to survive. The shortage, unavailability, and pollution of fresh drinking water is an emerging issue in almost every part of the world. To this end, the present study intends to evaluate the quality of groundwater and the associated health hazard risk of the Bankura district. To conduct the present study, 55 groundwater samples were collected across the Bankura district with intensive field investigation in the dry season, 2021 to assess the groundwater quality and associated health risks. For this study, we have selected 15 groundwater causative parameters to seek the NO3−, F− and Fe heavy metal groundwater quality (GWQ) status and impact of GWQ on human health by utilizing the degree of contamination (CD), GWQI and human health hazard index. Gibbs's diagram confirmed that the source of the groundwater pollutants is more geogenic than anthropogenic inputs for the Bankura district. The study's findings indicate that the GWQ of 25% area of the Bankura district is poor and unsafe for drinking purposes. In comparison, 15% of the groundwater contains good quality and is safe for drinking, and various pollutants moderately contaminate the remaining areas. The human health hazard index exhibited the same pattern as the GWQI map of the Bankura district. This unique finding of the present study will be helpful for the decision-makers, local well-being authorities and disaster management team to manage and mitigate the issue of GWQ of Bankura district and surroundings more sustainably.

Assessing the Susceptibility of Landslides in the Tuoding Section of the Upper Reaches of the Jinsha River, China, Using a Combination of Information Quantity Modeling and GIS

Combined with visible light remote sensing technology and InSAR technology, this study employed the fundamental principles of the frequency ratio model, information content model, and analytic hierarchy process to assess the susceptibility of the study area. Nine susceptibility assessment factors such as elevation, slope, aspect, water system, vegetation coverage, geological structure, stratum lithology, rainfall, and human activities were selected, and the factor correlation degree was calculated by using the relative area density value of the landslide. The frequency ratio model and information content model were selected to carry out landslide susceptibility zoning, and the accuracy of the two models was verified by the ROC curve and density method. The results indicate that the information content model performed relatively well. Therefore, the information model, combined with the analytic hierarchy process and fuzzy superposition method using the landslide point density map, was chosen to evaluate landslide susceptibility. The study area was divided into five levels of landslide hazard, ranging from low to high, using the natural discontinuity point method. The results show that the area of each hazard zoning is 197.48, 455.72, 408.21, 152.66, and 16.22 km2 from low to high, and the proportion of landslides in the corresponding area is 0.17%, 1.60%, 3.88%, 8.41%, and 16.65%, respectively. It can be seen that with the increase in the hazard level, the proportion of landslides also increases significantly, which verifies the accuracy of the hazard results. Additionally, four representative landslides in the study area were selected for analysis to understand their characteristics and underlying mechanisms. The results revealed that these landslides were notably influenced by the density of the Jinsha River and the surrounding roads. The susceptibility assessment outcomes for geological disasters align well with the current situation of landslide occurrences in the Tuoding river section, demonstrating high accuracy. This study provides a scientific foundation for effective prevention and control measures against local landslide disasters.