Spatial Risk Research Articles

Modeling Historic Arsenic Exposures and Spatial Risk for Bladder Cancer.

Arsenic is a bladder carcinogen though less is known regarding the specific temporal relationship between exposure and bladder cancer diagnosis. In this study, we modeled time-varying mixtures of arsenic exposures at many historic temporal windows to evaluate their association with bladder cancer risk in the New England Bladder Cancer Study. We used arsenic exposure estimates up to 60 years prior to study entry and compared the goodness of fit of models using these mixtures to those using summary measures of arsenic exposures. We used the Bayesian index low rank kriging multiple membership model (LRK-MMM) to estimate the associations of these mixtures with bladder cancer and estimate cumulative spatial risk for bladder cancer using participants' residential histories. We found consistent evidence that modeling arsenic exposures as a time-varying mixture provided better fit to the data than using a single arsenic exposure summary measure. We estimated several positive though not significant associations of the time-varying arsenic mixtures with bladder cancer having odds ratios (ORs) of 1.03-1.14 and identified many significant and positive associations for an interaction among those who consumed water from a private dug well (ORs 1.28-1.60). Arsenic exposures 40-50 years before study entry received elevated importance weights in these mixtures. Additionally, we found two small areas of elevated cumulative spatial risk for bladder cancer in southern New Hampshire and in south central Maine. These results emphasize the importance of considering time-varying mixtures of exposures for diseases with long latencies such as bladder cancer.

Spatial variation and potential ecological risk assessment of trace elements in the sediments of Chaohu Lake in China

Chaohu is a large freshwater lake. It plays an essential part in agriculture, life, and part of the industry. This study analyzed the heavy metals contents of copper (Cu), zinc (Zn), cadmium (Cd), mercury (Hg), arsenic (As), chromium (Cr), nickel (Ni), and lead (Pb) in sediments of the Chaohu Lake using inductively coupled plasma mass spectrometry. The distribution of some potential hazardous trace element in Chaohu Lake in the order as Zn (44.04 mg kg−1)>Cu (28.62 mg kg−1)>Cr (27.39 mg kg−1)>Pb (16.71 mg kg−1)≈Ni (16.22 mg kg−1)>As (5.89 mg kg−1)>Cd (0.14 mg kg−1)>Hg (0.04 mg kg−1). The results indicated that the selected heavy metals in the lake were practically uncontaminated, and the levels of selected potential hazardous elements varied from different sampling sites. Correlation analysis indicated that the selected potential hazardous element pollutant has co-contamination also occurs in sediments. However, in the center of Chaohu Lake, the primary contributor to the ecological risk was Cd (41%) and Hg (40%). Based on the PERI, the total potential ecological risk of selected heavy metals in the sediments of Chaohu Lake was light-contaminated.

Spatial distribution of heavy metals in the sediments of River Ganges, India: Occurrence, contamination, source identification, seasonal variations, mapping, and ecological risk evaluation

Present study analyzed the seasonal and spatial distribution patterns, sources, and ecological risks of seven heavy metals (Cr, Fe, Ni, Cu, Zn, Cd and Pb) in the sediments of River Ganges, finding that the majority of concentrations were lithologic, except for Cd, which was significantly higher than background standards. Elevated values of geochemical indices viz. Igeo, CF, RI, Cd, mCd, HQ, mHQ, and PN suggest moderate to high ecological risk in the benthic environment and its organisms due to the synergistic effect of heavy metals. The PEC-Qmetals revealed 8–10 % toxicity in the upstream and downstream sites, due to the influence of agricultural activities. Multivariate statistical techniques (PCM and PCA) indicated that Cd and Pb predominantly originated from anthropogenic sources, while other metals primarily derived from geological background. These geochemical findings may help to understand the potential risks and recommend strategies to mitigate the effects of metallic contamination in river sediments.

Health risk assessment of heavy metals in soils and crops in a mining area (Au-Ag-Cu-trona-oil et al.) of the Nanyang Basin, Henan Province, China

Heavy metal distribution in mining areas has always been a hot research topic due to the special environment of these areas. This study aims to explore the impact of heavy metal pollution on soils and crops in the study area, ensure the safety of local crops and the health of local residents, and provide a basis for the subsequent environmental restoration and the prevention and control of environmental pollution. Based on the analysis of the heavy metal concentrations in local soils and crops, the study investigated the spatial distribution, pollution degrees, and potential ecological risks of heavy metals in the farmland of a mining area in the southeastern Nanyang Basin, Henan province, China explored the sources of heavy metals and assessed the health risks caused by crop intake. The results of this study are as follows. The root soils of crops in the study area suffered heavy metal pollution to varying degrees. The degree of heavy metal pollution in maize fields is higher than that in wheat fields, and both types of fields suffer the most severe Cd pollution. Moreover, the root soils of different crops suffer compound pollution. The root soils in the maize fields suffer severe compound pollution at some sampling positions, whose distribution is similar to that of the mining area. Cd poses the highest potential ecological risks among all heavy metals, and the study area mainly suffers low and moderate comprehensive potential ecological risks. The principal component analysis (PCA) shows that the distribution of Zn, Cd, Pb, and As in soils of the study area is mainly affected by anthropogenic factors such as local mining activities; the distribution of Cr and Ni is primarily controlled by the local geological background; the distribution of Hg is mainly affected by local vehicle exhaust emissions, and the distribution of Cu is influenced by both human activities and the geological background. Different cereal crops in the study area are polluted with heavy metals dominated by Cd and Ni to varying degrees, especially wheat. As indicated by the health risk assessment results, the intake of maize in the study area does not pose significant human health risks; however, Cu has high risks to human health, and the compound heavy metal pollution caused by the intake of wheat in the study area poses risks to the health of both adults and children. Overall, the soils and crops in the study area suffer a high degree of heavy metal pollution, for which mining activities may be the main reason.©2023 China Geology Editorial Office.

Simulation of emergency evacuation with crowd-gathering risk and evaluation methods: a case study of the mass rapid transit system in Taipei

ABSTRACT Mass rapid transit (MRT) systems are the backbone of transportation infrastructure in many cities. During emergencies, indoor subway stations become particularly susceptible to panic and overcrowding, making evacuation difficult. Therefore, simulating the evacuation and sheltering processes of a large number of individuals during emergencies is key in urban disaster response. In this study, a spatial evacuation risk model was used to enhance the safety of evacuation strategies in an MRT system. Data were collected on spatial architectural floor plans, and a database for communication and pedestrian flow was established. The behavioral patterns and distribution of individuals within stations and the characteristics of refuge spaces were also investigated. To simulate the processes of evacuation and sheltering, the Pathfinder evacuation simulation tool was used to construct a three-dimensional spatial model of a subway station. Specific scenarios were then constructed to simulate the procedures of evacuation and sheltering. Subsequently, the factors contributing to overcrowding-related hazards were analyzed to examine the spatial risks associated with crowd aggregation and evacuation and provide recommendations for improvement. Given its numerous advantages, this approach can serve as a valuable reference for conducting risk assessments in other large-scale crowd aggregation spaces.

Spatial and temporal variability and risk assessment of organophosphate esters in seawater and sediments of the Yangtze River estuary

Organophosphate esters (OPEs) as substitutes for PBDEs have been widely detected in the marine environment, while little is known about the pollution characteristics and variation of OPEs in estuarine environments with complex hydrodynamic conditions and land-based input. Yangtze River Estuary (YRE) is a typical highly urbanized and industrialized estuary, with a complex hydrological environment and geochemical behavior. This study found that the concentrations of OPEs in both seawater and sediments in the YRE were higher in spring than in summer. Alkyl OPEs were the first contributor, with TnBP and TiBP as the main components, where the contribution of alkyl OPEs had exceeded 75 % in both seawater and sediments in spring, and 60 % in summer seawater, and even 80 % in sediments. In spring, OPEs peaked in the central to southern region near the YRE. In summer, OPEs were mainly concentrated in the southern branch waterway and southern nearshore area of the YRE and showed a decreasing trend to the northeast. The OPEs in the sediments were mainly concentrated in the Yangtze River Mud Area (YREMA) and the Zhe-Min Coastal Mud Area (ZMCMA). Based on the fugacity model and principal component analysis, sediments could be released into the aquatic environment as an endogenous source, and exogenous sources were mainly municipal and industrial sewage discharge sources, urban and marine traffic discharge sources, and atmospheric deposition sources. The ecological risk analysis showed that the Σ14OPEs had exhibited a low to moderate ecological risk in the southern branch waterway and the south-central region offshore.

Spatial distribution, ecological risk and sources of polycyclic aromatic hydrocarbons (PAHs) in water and bottom sediments of the anthropogenic lymnic ecosystems under conditions of diversified anthropopressure

Spatial distribution, ecological risk and sources of polycyclic aromatic hydrocarbons (PAHs) in water and bottom sediments of the anthropogenic lymnic ecosystems under conditions of diversified anthropopressure

Spatial dynamics and risk assessment of phosphorus in the river sediment continuum (Qinhuai River basin, China).

This study investigated the concentration and fractionation of phosphorus (P) using sequential P extraction and their influencing factors by introducing the PLS-SEM model (partial least squares structural equation model) along this continuum from the Qinhuai River. The results showed that the average concentrations of inorganic P (IP) occurred in the following order: urban sediment (1499.1 mg/kg) > suburban sediment (846.1-911.9 mg/kg) > rural sediment (661.1 mg/kg) > natural sediment (179.9 mg/kg), and makes up to 53.9-87.1% of total P (TP). The same as the pattern of IP, OP nearly increased dramatically with increasing the urbanization gradient. This spatial heterogenicity of P along a river was attributed mainly to land use patterns and environmental factors (relative contribution affecting the P fractions: sediment nutrients > metals > grain size). In addition, the highest values of TP (2876.5 mg/kg), BAP (biologically active P, avg, 675.7 mg/kg), and PPI (P pollution index, ≥ 2.0) were found in urban sediments among four regions, indicating a higher environmental risk of P release, which may increase the risk of eutrophication in overlying water bodies. Collectively, this work improves the understanding of the spatial dynamics of P in the natural-rural-urban river sediment continuum, highlights the need to control P pollution in urban sediments, and provides a scientific basis for the future usage and disposal of P in sediments.

Spatial distribution analysis and risk factors for stunting in Kerinci Regency, Jambi Province Indonesia

There are variations in the prevalence of stunting cases at the village level in Kerinci Regency. There have been no studies on the spatial distribution and risk factors of stunting cases in Kerinci Regency. This study aimed to determine the risk factors and spatial distribution of stunting. This research was conducted in Kerinci Regency from March to November 2020 using a case-control design and a total sampling technique. The study participants consisted of 223 patients and 223 controls. Children who experienced stunting were recorded at the health office. The controls were non-stunted children with an age range (±3 months) and sex who came from the same village as the cases—data collection through interview techniques and observation of the Mother and Child Health book. The chi-square test, logistic regression, and spatial distribution analysis were performed using the open-source software SatScan 10,1 and ArGIS 3,30. The analysis shows stunting cases clustered in Kayu Aro, Gunung Tujuh, and Keliling Danau Districts. A low father's education level (aOR=1,76), father's height <161 cm (aOR=1,52), mother's height <150 cm (aOR=1,83), and incomplete immunization status (aOR=1,6) were risk factors for stunting. In conclusion, cases of stunting clustered in three sub-districts, and the leading risk factor was the mother's height. The health office should make specific intervention efforts before and during pregnancy and focus on cluster-indicated areas.

Hepatitis A Chronic Immunity in Iran: A Geographic Information System-Based Study

Background: Chronic immunity to hepatitis A (HA) is largely influenced by environmental factors, such as socioeconomic indicators, public health conditions, and access to safe water. In the past two decades, Iran has witnessed improvements in socioeconomic status, increased urbanization, enhanced health education, improved access to safe drinking water sources, and better public health conditions. However, these changes have not been uniform across all regions of Iran, and varying epidemiological situations are expected. Objectives: This study aimed to delineate the pattern of HA chronic immunity across different regions of Iran using geographical information system (GIS) mapping. Methods: The study included a total of 3255 individuals who tested positive for anti-hepatitis A virus (anti-HAV) immunoglobulin G (IgG). This study analyzed factors such as place of residence, marital status, age, and gender to explore possible relationships. Univariate and multivariable analyses were conducted to identify independently associated factors for HA. A locally weighted scatterplot smoothing (LOWESS) multivariate model was developed using a backward stepwise approach. Geographical variations in the prevalence of HA chronic immunity in the general population of Iran were assessed to understand spatial effects and risk factors. A Bayesian spatial model was employed to identify the spatial pattern of HA chronic immunity prevalence, using OpenBUGS version 3.2.3. Results: The prevalence of HAV immunity was higher in regions with mild semi-dry climates (aPR = 2.37, 95% confidence interval [CI] = 2.30 - 3.33, P< 0.001), medium semi-dry climates (aPR = 1.37, 95% CI = 1.14 - 1.63, P< 0.001), dry climates (aPR = 1.13, 95% CI = 0.9 - 1.4), and ultra-dry climates (aPR = 1.79, 95% CI = 1.05 - 2.98, P = 0.033), compared to semi-humid climates. Other variables did not exhibit a significant relationship with HA chronic immunity. The GIS analysis map revealed that immunity to HA was generally lower in the capital cities of Iran’s provinces. However, most central regions of Iran exhibit medium endemicity; nevertheless, higher immunity to HA was observed in border areas and coastal regions, particularly in the northern part of the country. Conclusions: Different regions of Iran display distinct patterns of HAV endemicity, influenced by the country’s climatic diversity.

Spatial distribution characteristics, risk assessment and management strategies of tailings ponds in China

The tailings ponds (TPS) stemming from mineral resource exploitation are becoming a global challenge due to their high hazards and pollution to the surrounding area. However, previous studies on China's tailings ponds have either focused on a single or few areas, or the number of tailings ponds varies greatly. A systematic assessment of the number, distribution characteristics, potential risks and management strategies of the tailings pond in China is lacking. This study obtained the latest list of tailings ponds in China up to the end of 2022 based on official information and assessed their spatial distribution characteristics, environmental risk and management strategies simultaneously. The results demonstrated that the distribution of TPS in China is relatively clustered and multiple factors affected the spatial distribution of TPS in China, which were concentrated in areas with low economic and population density, convenient transportation, and a developed water system. The risk assessment suggested that 1803 TPS had large or significant environmental risks, which were mainly distributed in Yunnan, Hunan, Shaanxi and Jiangxi provinces. To solve the problem of tailings ponds from the source, the key point of tailings pond management in China should be adjusted from the prevention of pollution or dam break accidents to the full resource utilization of tailings. In summary, this study will provide a scientific basis for the risk control of TPS and an innovative idea for the management of other solid waste.

Forest Fire Dynamics in Nepal’s Mid-hills: Insights from Spatial Analysis and Risk Mapping of Doti District

Forest fires have significantly contributed to forest degradation and pollution all over Nepal. Despite their high severity, limited studies have been conducted on the spatial-temporal analysis and risk mapping of these fires especially in the Mid-hill region. This study aims to fill this gap by analyzing Visible Infrared Imaging Radiometer Suite (VIIRS) data from 2012 to 2022, along with satellite imagery, using remote sensing and geographic information systems (GIS) technology. Nine variables, including land class, distance to roads, proximity to settlements, temperature, wind speed, precipitation, slope, aspect, and elevation, were utilized to identify forest fire patterns and create a fire risk map. A multi-parametric hierarchical weighted index model was employed, with multicollinearity checked (VIF<2) to ensure model accuracy and validated by Area Under Curve (AUC=0.787). The study revealed an increasing trend of forest fires, particularly during March to May, in broad-leaved forests near human interference. Out of the total forested area of 1447.58 km2, 42.9%, 46.03%, and 11.07% were classified under high, moderate, and low-risk zones, respectively. The study emphasizes the recurring forest fire problem in often-neglected Mid-hill districts and underscores the need to prioritize them in future strategies.

Spatial analysis and risk factors of dengue hemorrhagic fever in Yogyakarta city, 2017-2018

Background: Dengue hemorrhagic fever (DHF) is a public health problem with high morbidity and mortality rates. These diseases are caused by the bite of the Aedes aegypti mosquito. Yogyakarta City is one of the endemic areas of DHF in Indonesia. This study aims to analyze the spatial distribution of DHF incidents and determine the risk factors associated with DHF incidence in Yogyakarta in 2017-2018. Methods: This was a descriptive quantitative with an ecological study design and using secondary data. Data was analyzed using statistical analysis and spatial analysis. Results: Spatial analysis shows that the DHF distribution does not follow the distribution of population density, house density, and larva-free rate. We found the population density (p value= 0.010, r = -0.661), house density (p value= 0.059, r = -0.516), and larva-free rate (p value= 0.907, r= -0.034). Conclusions: Spatially, there is no relationship between population density, house density, and larva-free rate to the DHF incidence in the City of Yogyakarta in 2017-2018. There is a relationship between population density and the incidence of DHF. In contrast, house density and larva-free rate have no association with the incidence of DHF in Yogyakarta in 2017-2018. The higher the population density, house density, and larva-free rate, the tendency for the incidence to decrease.

Spatial distribution and environmental risk of soil phosphorus under a long-term fertilizer strategy in a rice–wheat rotation system

Spatial distribution and environmental risk of soil phosphorus under a long-term fertilizer strategy in a rice–wheat rotation system

Occurrence, distribution and ecological risk assessment of herbicide residues in cropland soils from the Mollisols region of Northeast China

The first systematic and comprehensive investigation of herbicide residues was conducted by identifying their spatial distribution, influencing factors and ecological risk in cropland soils from the Mollisols region covering 109 million hm2 in Northeast China. Fifty-six herbicides were detected with total herbicide concentrations ranging from 1.01 to 1558.13 μg/kg (mean: 227.45). Atrazine, its degradates deethyl atrazine (DEA) and deisopropyl atrazine (DIA), trifluralin and butachlor were the most frequently detected herbicides, while DEA, clomazone, nicosulfuron, fomesafen, and mefenacet exhibited the highest concentrations. Despite being less frequently reported in Chinese soils, fomesafen, nicosulfuron, clomazone, and mefenacet were found widely present. Although most of the compounds posed a minimal or low ecological risk, atrazine, nicosulfuron and DEA exhibited medium to high potential risks. The key factors identified to regulate the fate of herbicides were soil chemical properties, amount of herbicides application, and the crop type. The soybean soils showed highest herbicide residues, while the soil mineral contents likely adsorbed more herbicides. This study provides a valuable large-scale dataset of herbicide residues across the entire Mollisols region of China along with fine-scale characterization of the ecological risks. Mitigation and management measures are needed to reduce the herbicide inputs and residues in the region.

Spatial distribution, ecological risk and health risk assessment of heavy metals in agricultural soil from Ankang basin, Shaanxi Province

In order to assess the heavy metal pollution features, ecological dangers, and health risk status posed to human beings by soils in the Ankang Basin, a study was conducted. This involved the collection of 38 surface soil samples, followed by the determination of elemental levels of arsenic, mercury, copper, cadmium, lead, chromium, nickel, and zinc. The concentrations of arsenic, mercury, copper, cadmium, lead, chromium, nickel, and zinc were quantified through the collection of 38 surface soil samples. The data obtained from the study was subjected to analysis and evaluation utilizing various academic methodologies, including the geo-accumulation index method, potential ecological risk assessment method, human health risk assessment model, and Monte Carlo simulation method. The findings indicated that the concentrations of the eight heavy metals in the soil above the background levels, with only Cadmium (Cd) marginally surpassing the threshold set for controlling soil pollution risks. The ground accumulation index revealed a higher degree of soil pollution with mercury, cadmium, copper, and zinc components. According to the possible ecological risk index, the presence of mercury and cadmium elements poses significant ecological hazards. The geographical distribution analysis suggests that these risks mostly stem from the combined impacts of human activities and the topographical and geomorphological characteristics of the river valley. The findings of the human health risk assessment indicated that the non-carcinogenic risk fell within acceptable limits. Additionally, it was observed that the carcinogenic risk associated with arsenic, mercury, cadmium, and nickel was comparatively greater for children as compared to adults. The results of the Monte Carlo simulations indicate that the non-carcinogenic hazards have a negligible effect on human health. However, it was seen that arsenic and nickel have a greater likelihood of presenting a substantial carcinogenic risk to humans, particularly in relation to the pediatric population, hence exerting a more pronounced impact on their health. In general, it is observed that conventional deterministic risk assessments tend to overstate the potential health risks associated with a given situation. Conversely, the utilization of Monte Carlo simulations has been found to effectively mitigate uncertainties in health risk assessments. It has been observed that children exhibit a higher vulnerability to both carcinogenic and non-carcinogenic health impacts resulting from exposure to heavy metals present in soil, in comparison to adults. It is recommended that residents prioritize the surveillance of soil heavy metals in relation to potential impacts on human health.

Spatial and temporal patterns and risk assessment of carbon source and sink balance of land use in watersheds of arid zones in China - a case study of Bosten Lake basin

In recent years, Northwest China has experienced rapid land-use transformation and urbanization. Land-use carbon emissions associated with human activities are an important cause of climate change. However, the carbon sources and sinks associated with land-use change in arid zone watersheds need further study. This study focuses on Bosten Lake in Northwest China and employs a combination of top-down and bottom-up methods to assess the spatial and temporal evolution of carbon source and sink balance under land use changes and identify areas with high carbon emission risks. The key discoveries are as follows: (1) The land use category shows a pattern of “three decreases and three increases.” Grassland, unused land, and water area have decreased, while construction land, arable land, and forest land have increased. Cultivated land shows significant expansion, with an increase of 2375.71 km2. The overall distribution of land use intensities breaks through traditional boundaries, resulting in more dispersed reorganization of land use types. (2) Carbon emissions originating from land use category exhibit an upward trend, with a net increase of 1413.38 × 104 t. Construction land emerges as the primary carbon source, while arable land experiences the highest rate of carbon source migration. Grassland serves as the primary carbon sink migration area. Transformations and rapid expansions of arable land contribute significantly to changes in carbon balance. (3) Carbon emission risks are prominent in agricultural and pastoral areas as well as urban core regions, gradually decreasing in surrounding areas with a single-core staggered distribution pattern. The carbon source exceeds the carbon absorption, indicating a significant imbalance in carbon balance. These findings carry significant implications for the promotion of low-carbon and high-quality development in the Bosten Lake basin and the optimization of national territorial planning.

Undernutrition among children and its determinants across the parliamentary constituencies of India: a geospatial analysis.

In India, undernutrition among children has been extremely critical for the last few decades. Most analyses of undernutrition among Indian children have used the administrative boundaries of a state or a district level as a unit of analysis. This paper departs from such a practice and focuses instead on the political boundaries of a parliamentary constituency (PC) as the unit of analysis. The PC is a critical geopolitical unit where political parties and party candidates make election promises and implement programmes to improve the socio-economic condition of their electorate. A focus on child undernutrition at this level has the potential for greater policy and political traction and could lead to a paradigm shift in the strategy to tackle the problem by creating a demand for political accountability. Different dimensions and new approaches are also required to evaluate the socio-economic status and generate concrete evidence to find solutions to the problem. Given the significance of advanced analytical methods and models embedded into geographic information system (GIS), the current study, for the first time, uses GIS tools and techniques at the PC level, conducting in-depth analysis of undernutrition and its predictors. Hence, this paper examines the spatial heterogeneity in undernutrition across PCs by using geospatial techniques such as univariate and bivariate local indicator of spatial association and spatial regression models. The analysis highlights the high-low burden areas in terms of local hotspots and identifies the potential spatial risk factors of undernutrition across the constituencies. Striking variations in the prevalence of undernutrition across the constituencies were observed. Most of these constituencies that performed poorly both in terms of child nutrition and socio-economic indicators were located in the northern, western, and eastern parts of India. A statistically significant association of biological, socio-economic, and environmental factors such as women's body mass index, anaemia in children, poverty, household sanitation facilities, and institutional births was established. The results highlight the need to bring in a mechanism of political accountability that directly connects elected representatives to maternal and child health outcomes. The spatial variability and pattern of undernutrition indicators and their correlates indicate that priority setting in research may also be greatly influenced by the neighbourhood association.

Spatial risk assessment of maritime transportation in offshore waters of China using machine learning and geospatial big data

Maritime transportation plays a crucial role in global trade and economic development. However, this industry is exposed to various risks (e.g., natural disasters), which can cause significant economic and environmental damage. This study aims to develop a spatial risk assessment approach for maritime transportation using machine learning and geospatial big data to identify potential risks in China's maritime transportation industry. The proposed approach first produces risk maps that reveal significant variability in maritime transportation risks across different regions of China. Then, factor importance analysis identifies wave height, rainfall, and sea surface temperature as the most influential factors affecting navigational safety. Finally, capability indicators are employed to analyze the matching relationship between coastal search and rescue resources and maritime transportation risks. Our study provides valuable references for enhancing maritime emergency response capabilities and protecting marine ecological environments.

Spatial Risk Assessment of the Effects of Obstacle Factors on Areas at High Risk of Geological Disasters in the Hengduan Mountains, China

The Hengduan Mountains in China are known for their complex geological environment, which leads to frequent geological disasters that pose significant threats to the safety and economic and social development of the local population. In this study, we developed develop a multi-dimensional evaluation index system from the aspects of economy, society, ecology, and infrastructure, and the resilience inference measurement (RIM) model was developed to assess resilience to regional disasters. The clustering evaluation of exposure, damage, and recovery variables in four states was conducted by way of K-means clustering. The results of K-means clustering are confirmed by discriminant analysis, and the disaster resilience index was empirically verified once. At the same time, the obstacle factor was further analyzed with the obstacle degree model. The results indicate that there are 8 susceptible areas, 23 recovering areas, 27 resistant areas, and 7 usurper areas. The classification accuracy of the model is 95.4%. The disaster resilience of high-risk areas was found to be low, with “extremely poor” differentiation, where the majority of the areas had low resilience and only a minority had high resilience. A “high in the southeast and low in the northwest” spatial distribution was observed. High-resilience areas were “dotted” and mainly concentrated in core areas with a high population density and strong economic activity, while low-resilience areas had a pattern of “edge extension” and were mainly distributed in the transition zone between the Qinghai–Tibet and Yunnan Plateaus. There were clear differences in the barriers of disaster resilience among the 65 counties (cities). The economic barrier degree was found to be the largest barrier to disaster resilience, followed by ecological, social, and infrastructure barrier degrees. The main factors affecting the distribution of disaster resilience in the high-risk areas were topographic relief, proportion of female population, cultivated land area, industrial structure, number of industrial enterprises above a designated size, and drainage pipeline density in the built-up area. Additionally, primary barrier factors classify the 65 counties (cities) into three types: economic constraint, natural environment constraint, and population structure constraint.