Analysis On The Spatial Differentiation Characteristics of Poverty Risk Caused By Disaster Under The Stress of Geological Disasters – A Case Study of Sichuan Province

Research on the poverty risk caused by disasters in disaster - prone areas is a useful exploration to coordinate social economic development with disaster prevention and reduction, and is of great significance to regional sustainable development. Based on statistical data and spatial data, this paper takes Sichuan Province as the typical research area. Remote sensing and geographic information technology are used to study the poverty risk caused by disasters based on the quantitative evaluation of geological disasters risk and regional development level. the spatial differentiation characteristics of poverty risk caused by disasters are explored on the 1 km × 1 km grid scale. The results indicate that: (1) The overall risk of geological disasters in Sichuan Province is relatively high, with high and relatively high risk areas accounting for more than 40%, low and relatively low risk areas accounting for less than 30%. The risks in Mountain and Ravine Areas are significantly higher than other areas. (2) The regional development level in Sichuan Province is relatively high, but with significant the spatial differences. The development level of high-altitude areas and remote mountainous areas is quite different from that of the Chengdu Plain in the middle Sichuan Province. the problem of uneven development in the east, middle, and west is prominent. (3) The poverty risk caused by disasters is high, and the spatial pattern presents a characteristic of “high in the west and low in the east” with high positive spatial correlation. High - High Cluster Areas are mainly distributed in western and southwestern Sichuan. Low - Low Outlier Areas are mainly distributed in Chengdu Plain and Hilly Areas of Sichuan Basin. High - Low Outlier and Low - High Outlier Areas occupy a relatively small percentage with scattered distribution. This paper provides a reference for the coordinated management of disaster prevention and reduction, as well as social and economic development in underdeveloped areas.

Quantitative Risk Assessment and Application of Landslide Disaster in Chongqing

Chongqing is located in southwestern China, and geological disasters occur frequently. The amount of potential landslide disasters is far greater than the number of landslides that can be managed by government funds, so the risk assessment for potential landslide disasters is critical. In practical applications, risk assessment methods based on landslide stability and loss are restricted by various factors. These methods can be simplified to semi-empirical assessment methods, which are influenced by the discrimination factors near the limit values of the determined conditions, possibly leading to sudden changes in the evaluation results and distort the conclusions. To solve this problem, we propose a full quantitative risk assessment method according to the probability of landslide damage. The mathematical probability model is used to quantitatively describe the risk assessment impacting factors, weaken the boundary influence, and improve the accuracy of landslide risk assessment. Correspondingly, the software is developed to conduct quantitative risk assessment on six landslides in Feng jie County, Chongqing, which verifies the accuracy and reliability of the full quantitative risk assessment method, and provides an important reference for judging urban landslide geological disasters.

Research on the Application of GIS Technology Combined with RBFNN-GA Algorithm in the Delineation of Geological Hazard Prone Areas

With the rapid development of the economy and society, geological disasters such as landslides, collapses, and mudslides have shown an intensifying trend, seriously endangering the safety of people’s lives and property, and affecting the sustainable development of the economy and society. Aiming at the problems of merging different data layers and determining the weighting of data stacking in the statistical analysis model based on GIS technology in the evaluation of the risk of geological disasters, this study proposes a logistic regression model combined with the RBFNN-GA algorithm, that is, the determination of the occurrence of geological disasters. The fusion coefficient (CF value) with the RBFNN-GA algorithm model, and with the help of SPSS statistical analysis software, solves the problem of factor selection, heterogeneous data merging, and weighting of each data layer in the risk assessment. In the experimental stage, this study adopts the method of geological hazard certainty coefficients to carry out the sensitivity analysis of the geological hazards in the study area. Using homogeneous grid division, the spatial quantitative evaluation of the risk of geological disasters is realized, and at the same time, the results of the spatial quantitative evaluation of the risk of geological disasters are tested according to the latest landslide points in the region. The existing classification mainly depends on the acquisition of land use/cover information or the processing method of the acquired information, but the existing information acquisition will be limited by time, space, and spectral resolution. The results show that the number of landslide points per unit area in the extremely unstable zone and the unstable zone is 0.0395 points/km2 and 0.0251 points/km2, respectively, which is much higher than 0.0038 points/km2 in the stable zone, indicating the evaluation results and actual landslide conditions.

Dual-Frequency Induction Polarization Electric Field Focusing Based on Intelligent Algorithm for Coal Mine Electric Exploration

As the most important and dangerous front-end production link, coal mining operations will inevitably face geological disasters such as water inrush, rock burst, collapse, and fire, posing a great threat to the life and safety of miners. Among the five major geological disasters (gas, dust, water, fire, roof) in coal mines, the threat of flooding is very serious and it is one of the main disasters in coal mines. The research and development of dual-frequency excitation technology and its application in coal mine exploration have realized the elimination of potential safety hazards, improved the work efficiency and safety factor of prospectors, and realized the automated operation of the exploration process. This article explores the electric field of the intelligent algorithm’s focused dual-frequency induced polarization method in coal mine electrical exploration, and summarizes some of the advantages of the intelligent algorithm’s focused dual-frequency induced polarization method in coal mine surveying on related materials, and then conducts related experiment, through the experiment of focusing on the dual-frequency IP method in the coal mine survey, obtained the result, in the abnormal point detection experiment, the change trend of the two curves is the same, the increase is more obvious at 1.3-1.5m, and at 1.5m When reaching the limit value, when it exceeds 1.5m, it starts to fall. It shows that when there is a water-bearing anomalous body directly in front of the tunneling section, the measurement results of the two survey lines are roughly the same. Compared with the no anomaly body, the apparent resistivity and the apparent amplitude frequency both change significantly, and reach the extreme in a certain direction. However, the actual anomalous body is located 1.0m directly in front of the tunneling section, which means that the actual position of the anomaly cannot be determined based on the apparent resistivity and the extreme point position of the apparent amplitude frequency.

Study on debris flow risk monitoring and Early Warning in Nujiang Prefecture, Yunnan Province, China

Debris flow is the mainly the geological disasters in Nujiang Prefecture, while precipitation is the trigger of it, how to implement debris flow forecast based on precipitation monitoring data or forecast data is a hot issue in current debris flow disaster research field. Because of the special geomorphology in Nujiang Prefecture, due to the influence of human activities, geological disasters occur frequently, severely affect the local economic development. As a demonstration area of geological disaster monitoring and early warning in Yunnan Province, to build a well-developed geological disaster warning system, it is very important to spread it to other parts of Yunnan province. Based on the analysis of the current situation of geological disasters in Nujiang Prefecture, adopt appropriate monitoring method and calculation method to select the primary sites for debris flow monitoring and early warning in the Nu River basin for research.

Description of the dynamics of the resilience of people victims of the 2018 North Lombok earthquake

Before the earthquake struck lombok island on July 26, 2018, with a magnitude of 6.4 SR and on August 5, 2018 with a magnitude of 7.0 SR, it turned out that the history of earthquakes in Lombok had occurred 7 times from 1856 to 2013 with different strengths. So it can be concluded that lombok island is classified as a disaster prone area. Earthquakes include geological disasters that leave major impacts on lives, economies, infrastructure, the environment as well as psychological impacts. This research aims to describe the dynamics of the resilience of the victims of the 2018 North Lombok earthquake. This research aims to describe the dynamics of the resilience of the victims of the 2018 North Lombok earthquake. This article was compiled using two sections using literature studies and empirical research with a qualitative approach through in-depth interview motode. The results showed that the dynamics of resilience formation in earthquake victims had a profound effect on the success of synergy holistically both individual strength factors in mitigation implementation, family support factors and community factors both in a broad and narrow environment. The aspects of resilience in lombok society are the dominant aspects of optimism, empathy, self-efficacy and reaching out.

Risk Assessment of Pipeline Engineering Geological Disaster Based on GIS and WOE-GA-BP Models

Oil and gas pipelines are part of long-distance transportation projects which pass through areas with complex geological conditions and which are prone to geological disasters. Geological disasters significantly affect the safety of pipeline operations. Therefore, it is essential to conduct geological disaster risk assessments in areas along pipelines to ensure efficient pipeline operation, and to provide theoretical support for early warning and forecasting of geological disasters. In this study, the pipeline routes of the Sichuan-Chongqing and Western Hubei management offices of the Sichuan-East Gas Transmission Project were studied. Seven topographic factors—surface elevation, topographic slope, topographic aspect, plane curvature, stratum lithology, rainfall, and vegetation coverage index—were superimposed using the laying method with a total of eight evaluation indicators. The quantitative relationships between the factors and geological disasters were obtained using the geographic information system (GIS) and weight of evidence (WOE). The backpropagation neural network (BP) was optimised using a genetic algorithm (GA) to obtain the weight of each evaluation index. The quantified index was then utilized to identify the geological hazard risk zone along the pipeline. The results showed that the laying method, stratum lithology, and normalised difference vegetation index were the factors influencing hazards.