Low Risk Zones Research Articles

Later Life as a Daring Experience: Factors Associated with Older Adults’ Risk Perception

ABSTRACT Risk perception refers to people’s subjective judgments about the possibility of negative occurrences and the extent to which they are concerned with them. Previous studies have found that older adults who were exposed to ongoing terror threats developed later-life and terror risk perceptions. These studies showed that high risk perception has negative psychological and physiological consequences. This study aimed to identify the factors associated with the development of both later-life risk perception and terror risk perception in later life. Data were collected via an online survey with 306 Internet users aged 50 years and over, half resided in a high-risk zone while the remainder lived in a low-risk zone. The Perceived Risk Scale, measures of depressive symptoms, life satisfaction, social support, spirituality, internet use, and personal background were applied. Low self-rated health was associated with terror and later-life risk perceptions, regardless of the risk zone. After controlling for personal background, only depressive symptoms significantly correlated with high risk perceptions. These findings suggest that older adults with poorer self-rated health, secular beliefs, and elevated depressive symptoms may be susceptible to developing high risk perceptions. Clinicians should encourage older adults to identify preserving resources to improve adjustment to late life stressors.

Exploring Spatio-Temporal Variations of Ecological Risk in the Yellow River Ecological Economic Belt Based on an Improved Landscape Index Method.

Intense human activities have led to profound changes in landscape patterns and ecological processes, generating certain ecological risks that seriously threaten human wellbeing. Ecological risk assessment from a landscape perspective has become an important tool for macroecosystem landscape management. This research improves the framework and indices of the ecological risk assessment from a landscape perspective, evaluates the land use pattern and landscape ecological risk dynamics in the Yellow River Ecological Economic Belt (YREEB), analyzes the spatiotemporal variation, and identifies key areas for ecological risk management. The results indicate the following: The main land use types in the region are grassland and cropland, but the area of cropland and grassland decreased during the study period, and with the accelerated urbanization, urban land is the only land use type that continued to increase over the 20-year period. The ecological risk in the YREEB tended to decrease, the area of low ecological risk zones increased, while the area of high ecological risk zones gradually decreased. Most areas are at medium risk level, but the risk in central Qinghai and Gansu is obviously higher, and there is a dispersed distribution of local high- and low-risk zones. A total of 37.7% of the study area is identified as critical area for future risk management, and the potential for increased risk in these areas is high. These results can provide a basis for sustainable development and planning of the landscape and the construction of ecological civilization in ecologically fragile areas.

Monitoring and Assessment of SBAS-InSAR Deformation for Sustainable Development of Closed Mining Areas—a Case of Nanzhuang Mining Area

Closed mining areas are an important potential resource, and rational use of them are critical to implementing sustainable development strategies. To guide the more reasonable development and utilization of the closed mining areas, we proposed a method of surface deformation monitoring and subsidence risk assessment of the closed mining areas with SBAS-InSAR technology. Based on the analysis of deformation, a risk assessment model integrating subsidence hazard and subsidence vulnerability was proposed. Subsidence hazard include accumulate deformation and the subsidence rate of the last year. The tunnels and the land use types are used to assess the subsidence vulnerability. This method can achieve deformation monitoring and risk assessment of the closed mining areas, and the proposed method is validated by taking the Nanzhuang mining areas as an example. The results showed that the main subsidence areas in the closed mining areas are located in the tunnel in the southwest and the gangue pile area in the northeast of the mining areas, while the deformation in the vegetation-rich forested area is low. The area of low, medium and high subsidence risk zones is 65.5%, 27.8% and 6.7% respectively.

Revealing the geomorphic parameters of neotectonics based on geological and seismic data at Wadi Beda basin, NW Gulf of Suez, Egypt

The current study used remote sensing, GIS, and seismic data to determine the geological and morphometric parameters of the Wadi Beda Basin area, which is located in the northwestern part of the Gulf of Suez Province. The geomorphic parameters related with the development of neotectonics are deduced using the Shuttle Radar Topography Mission (SRTM), DEM-derived catchments, and drainage networks of the research area. The most important geomorphic parameters applied to the current study area are valley floor width to height ratio (Vf), stream length gradient index (Sl), transverse topographic symmetry index (T), hypsometric curve and integral (HI), and drainage basin shape (Bs). Based on the obtained geomorphic parameter results, the Wadi El-Noqra and Wadi Umm Athala basins exhibit moderate tectonic activity and moderate symmetry and are considered to be at their mature stage. The main basins of Wadi Umm Elda and Wadi Beda are moderately symmetrical and reflect the youth stage. However, the Bs index suggests that the Beda main basin has moderate tectonic activity, whereas Wadi Umm Elda has strong tectonic activity. By integrating the geomorphic and geological data, it is possible to determine that the majority of the study area (83.4%) is categorized by a moderate risk. Low-risk and high-risk zones, on the other hand, make up 11.1% and 5.5%, respectively, of the study area. The majority of the wadis in the Wadi Beda Main Basin are controlled by NW-trending faults, and the perturbation sites are concentrated there where these faults cross with E-W-trending faults, making them high-risk areas.

Delineating and identifying risk zones of soil heavy metal pollution in an industrialized region using machine learning

The ability to control the risk of soil heavy metal pollution is limited by the inability to accurately depict their spatial distributions and to reasonably delineate the risk zones. To overcome this limitation and develop machine learning methods, a hybrid data-driven method supported by random forest (RF) and fuzzy c-means with the aid of inverse distance weighted interpolation was proposed to delineate and further identify risk zones of soil heavy metal pollution on the basis of 577 soil samples and 12 environmental covariates. The results indicated that, compared to multiple linear regression, RF had a better prediction performance for As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, with the corresponding R2 values of 0.86, 0.85, 0.78, 0.85, 0.84, 0.78, 0.79 and 0.76, respectively. The relative concentrations (predicted concentrations divided by risk screening values) of Cd (17.69), Cr (1.38), Hg (0.31), Pb (6.52), and Zn (8.24) were relatively high in the north central part of the study area. There were large differences in the key influencing factors and their contributions among the eight heavy metals. Overall, industrial enterprises (21.60% for As), soil pH (31.60% for Cd), and population (15.50% for Cr) were the key influencing factors for the heavy metals in soil. Four risk zones, including one high risk zone, one medium risk zone, and two low risk zones were delineated and identified based on the characteristics of the eight heavy metals and their influencing factors, and accordingly discriminated risk control strategies were developed. In the high risk zone, it will be necessary to strictly control the discharge of heavy metals from the various industrial enterprises and mines by the adoption of cleaner production practices, centralizedly treat the domestic wastes from residents, substantially reduce the irrigation of polluted river water, and positively remediate the Cd, Cr, and Ni-polluted soil.

GIS-based risk assessment of tropical surface water pollution by integrating hydrogeological and anthropogenic parameters

Surface water pollution is a huge issue worldwide that keeps growing in magnitude and complexity which leads to millions of people don’t have access to clean water resource. Numerous studies on vulnerability, hazard and risk assessment of water pollution had been conducted yet most of them only focused on one of the three risk components. Therefore, the objective of this study was to apply a geospatial approach that integrated hydrogeological and anthropogenic parameters to assess the risk of surface water pollution in Selangor River Basin, Malaysia. Analytical Hierarchy Process (AHP) and Weighted Linear Combination (WLC) were applied in hydrogeological vulnerability assessment. WRASTIC index was used in anthropogenic hazard assessment. The risk map showed that high-risk zones were mainly located in areas where development and agricultural activities are extensive. Conversely, low-risk zones were in areas that were mostly covered by forest with few developments, such as the upstream region. The results also revealed that high and very risk levels were dependent on soil media and presence of land use and anthropogenic activity especially agriculture, industry, and wastewater presence. The risk map also showed that developed area with high hydrogeological vulnerability would have higher risk of pollution compared to areas without any anthropogenic hazard. The risk map can assist stakeholders to identify at risk of pollution. This allows for better decision-making in integrated river basin management.

“Flood risk modeling in southern Bagmati corridor, Nepal” (a study from Sarlahi and Rautahat, Nepal)

Flooding is underlying major natural hazard of Nepal and hence socio-economic loss has been paid annually by this hazard. Planning and management of flood based on study is still lack in Nepal. So, the particular study is carried out to assess the flood risk modeling in lower Bagmati river region in Eastern Terai. In this study, total 10 geospatial environment layers and past flood inventory from field were used to run the machine learning model i.e., MaxEnt for risk modeling of flood. The past flood data were separated into 75% for model building and 25% for model validation. The land use land cover change showed the highest contribution (40.8%) to the flood while the lowest contribution was of slope only 0.2%. 9% of total population were in high risk of flood while 39% population were in very low risk. Figure no. 13 shows that 5% of total household were in high risk, 55% were in moderate risk and 20% were in very low risk of flood. Out of total study area about 2.66% of the total area is in very high-risk zone to flood. High risk zone is found to be 4.89%, where as 9.48%, 20.61% and 62.36% are moderate, low, and very low risk zone area. In terms of AUC values, acceptable results were obtained for the test data with 0.931 and the standard deviation 0.019. The values of Area Under Curve (AUC) range from 0.7 to 0.8 and interpreted as fair or good. Finally, this research could directly help in policy, planning, framework, and programming of development intervention to tackle with flood hazard.

Comparing donor and recipient total cardiac volume predicts risk of short-term adverse outcomes following heart transplantation.

In pediatric heart transplantation, donor: recipient weight ratio (DRWR) has long been the sole metric for size matching. Total cardiac volume (TCV)-based size matching has emerged as a novel method to precisely identify an upper limit of donor organ size of a heart transplant recipient while minimizing the risk of complications from oversizing. The clinical adoption of donor: recipient volume ratio (DRVR) to prevent short-term adverse outcomes of oversizing is unknown. The purpose of this single-center study is to determine the relationship of DRWR and DRVR to the risk of post-operative complications from allograft oversizing. Recipient TCV was measured from imaging studies and donor TCV was calculated from published TCV prediction models. DRVR was defined as donor TCV divided by recipient TCV. The primary outcome was short-term post-transplant complications (SPTC), a composite outcome of delayed chest closure and prolonged intubation > 7 days. A multivariable logistic regression model of DRWR (cubic spline), DRVR (linear) and linear interaction between DRWR and DRVR was used to examine the probability of experiencing a SPTC over follow-up as a function of DRWR and DRVR. A total of 106 transplant patients' records were reviewed. Risk of the SPTC increased as DRVR increased. Both low and high DRWR was associated with the SPTC. A logistic regression model including DRWR and DRVR predicted SPTC with an AUROC curve of 0.74. [95% CI 0.62 0.85]. The predictive model identified a "low-risk zone" of donor-recipient size match between a weight ratio of 0.8 and 2.0 and a TCV ratio less than 1.0. DRVR in combination with DRWR predicts short-term post-transplant adverse events. Accepting donors with high DRWR may be safely performed when DRVR is considered.

Debris Flow Hazard Assessment in District Chitral, Eastern Hindu Kush, Pakistan

The aim of this study is debris flow risk zonation using geological and hydrometeorological indicators in district Chitral, Hindu Kush Region Northwest Pakistan. The research is based on secondary data. Multi criteria Analysis (MCA) in Geographical Information System (GIS) environment was used to achieve the objective of the study. The geological and hydrometeorological parameters were analyzed by making five classes of each parameter. The classes are ranked as most favorable and least favorable with numerical weights. The weights were assigned in accordance to their importance in debris flow occurrence. Then weighted overlay analysis techniques were applied to develop composite map representing the importance of each factor. Debris flow risk zonation map was resulted into four classes very high risk zones, high risk zone, moderate zone, low risk zone. The geology of the study area is diverse with frequents earthquakes. Similarly the forest cover is decreasing due to anthropogenic activities. The area is also characterized by long cold winters with frost action. These factors are destabilizing the slope. During summer season rain storm event results high surface runoff and peak discharge in the perennial and non-perennial channels which results flood and debris flow. These events result human life loss and disruption. The main villages located in very high risk zone are Mulkoh, Mastuj, Reshun, Shegram, Terich Gol, Rogar, Asurat, Boni, Brep and Rech Tockhow. They have been frequently affected by hazard in the past decade. Out of the total area, very high risk zone is expanded over 8%, high risk zone is expanded over16%, moderate risk zone is 29% and the rest is low risk zone. This study has highlighted the risk zones which will help disaster management authorities and policy makers to reduce the risk of debris flow in future.

Integrated flood risk assessment of river basins: Application in the Dadu river basin, China

Flood is the most common worldwide natural disaster with enormous impacts on human society and the ecosystem. Consequently, the research of flood risk assessment and zonation is critical. Its research scope is changeable, wherein the basin-scale research has become more and more important due to the increasing boom of cascade hydropower development in the river basin. The study proposed a basin-wide integrated flood risk assessment method combining index-based evaluation, Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) technologies, which was implemented in the Dadu River basin, southwestern China to assess and zoning the basin flood risk. In the constructed risk assessment index system, we use extreme rainfall and dam breach to jointly describe the basin flood disaster-inducing factors and select flood control standard and flood routing coefficient as the sub-indicators of basic and specific coping capacity to characterize the flood intervention capacity of hydropower engineering. The results showed that, for the hazard, vulnerability and risk zonation maps with five classified levels, the southern of midstream and downstream of the basin are prone to frequent floods, while higher vulnerability levels mainly concentrate in the downstream but some parts scatter in the medium vulnerability zone. The high and very high risk zones account for 3% of the basin area and mainly concentrate in the southern basin, while 86% of the basin area is assigned as low and very low risk zones. The results of this work quantitatively express the spatial distribution characteristics of basin-wide flood hazard, vulnerability and risk, and provide a reference for practicing an integrated and efficient flood risk management, and disaster prevention and alleviation strategies.

Mapping the forest fire risk zones using artificial intelligence with risk factors data.

Geographical information system data has been used in forest fire risk zone mapping studies commonly. However, forest fires are caused by many factors, which cannot be explained only by geographical and meteorological reasons. Human-induced factors also play an important role in occurrence of forest fires, and these factors depend on various social and economic conditions. This article aims to prepare a fire risk zone map by using a data set consisting of 11 human-induced factors, a natural factor, and temperature, which is one of the risk factors that determine the conditions for the occurrence of forest fires. Moreover, k-means clustering algorithm, which is an artificial intelligence method, was employed in preparation of the fire risk zone map. Turkey was selected as the study area because there are social and economic variations among its regions. Thus, the regional forest directorates in Turkey were separated into four clusters as extreme-risk zone, high-risk zone, moderate-risk zone, and low-risk zone. Also, a map presenting these risk zones were provided. The map reveals that, in general, the western and southwestern coastal areas of Turkey are at high risk of forest fires. On the other hand, the fire risk is relatively low in the northern, central, and eastern areas.

Establishing a low-risk zone for a temporary extra-articular calcaneo-tibial pin fixation in an unstable ankle or subtalar joint

This study aimed to establish a low-risk zone to avoid neurovascular injury during a temporary extra-articular calcaneo-tibial pin fixation in an unstable ankle or subtalar joint. A line from the calcaneal tuberosity center to the lateral end of the posterior malleolus at the ankle joint level defines the lateral border of this zone. Another line from the calcaneal tuberosity center to the midpoint of the anterior distal tibial articular surface at the joint level defines its medial border. This region was assumed to have a low neurovascular injury risk upon pin insertion. Fifty ankles from 50 patients who had undergone magnetic resonance imaging (MRI) for ankle disorders were assessed. T1-weighted oblique axial MRI slices were oriented to the pin trajectory. The mean distances between the sural nerve and the lateral border of the low-risk zone and between the posterior tibial neurovascular structures and the medial border of the low-risk zone were 15.0 ± 2.5 (range 9.1 to 21.1) and 12.8 ± 2.6 (6.3 to 20.8) mm, respectively. No neurovascular structures were identified within the low-risk zone. These findings demonstrated that an unstable ankle or subtalar joint can be temporarily fixated with an extra-articular calcaneo-tibial pin at a defined zone with a low neurovascular injury risk.

Investigation of fire risk zones using heat–humidity time series data and vegetation

Forest fires destroy these areas and have devastating and harmful socio-economic and environmental effects. One of the methods of preventing and managing the hazards created in the field of forest fires is to determine the range of fire risk. The purpose of this study is to determine the high-risk areas of fire in the forests of Golestan province using remote sensing data and field information. For this purpose, the data of MODIS satellite during the years 2005 to 2020 for the middle of November to mid-February, which is the peak of the fire occurrence, were prepared. (NDVI) vegetation index, (NDMI) plant moisture stress index and (LST) land surface temperature were extracted as a 15-year average in these months. Then, using precipitation data from meteorological stations, precipitation index (SPI) was calculated as an average to estimate the amount of drought for the mentioned years. By combining the mentioned indices, the areas with fire risk were extracted. Then, previous fire reference data were used to validate the obtained results of the study. The results of fire potential map evaluation showed that about 6.39% of the area has very high potential, indicating that about 65.78% of fire risk points have been located in this area and about 56.32% of the area is in moderate-fire-risk position, encompassing about 23.16% of the areas with fire risk. Finally, a low-risk zone encompassing 36.34% of the area, which about 11.06% of the high-fire-risk areas are located in this area. Also, the indices of NDMI, NDVI, SPI and LST precipitation have a degree of correlation of 74. 58%, 60.1%, 47.11% and 41. 02% with the map of fire points, respectively.

Analyzing flash flood risk in a section of ntawogba creek, Port Harcourt city, Rivers State

Flood is a natural disaster and occurred in different forms. It is also a factor of climate change. Flash flood is a type of flood that occurs within few hours of intensive precipitation. It poses serious threat to urban areas, particularly in less developed countries. Geospatial technology has been very useful in mapping spatial extent and quantified damages associated with flash flood events. Proximity analysis and AHP has been widely utilized in modeling flash flood vulnerable zones. Little was known about MCA ranking method which is considered appropriate for few parameters in making complex decisions. This study utilized MCA ranking method to analyzed flash flood risk within Ntawogba Creek, Port Harcourt, Rivers State. Rainfall, slope model, impervious surface and distance to river were used in the decision making. The datasets were processed into common spatial referenced system. Each criterion was scaled from 5 to 1, with 5 being very high risk and 1 very low risk area. Weights were assigned to the criteria based on the importance, with higher weight to criterion that is more important in the decision making process. The weights are; distance to water channel 48, impervious surface 25, slope 22 and rainfall 5. The results obtained showed area of 93.0ha as very high flash flood risk representing 6% of the area. This zone was located along Ntawogba Creek and on major roads. Total area of high risk zone was 864.1ha representing 56%, moderate risk and low risk zone was 452.2ha and 134.7ha with 29.3 5 and 8.7% respectively. For further study, drainage density and soil infiltration should be included in the flash flood risk analysis.

Ecological Risk Assessment of Oil Spill Events Using a Coupled Geospatial and Weight of Evidence Data-Process Model

This research work applied geospatial and weight of evidence approach to ecological risk assessment for quantifying environmental exposure to oil pollution in the Niger Delta. Spatial data for Pipelines, Oil spills and Land Cover were used to quantify the extent of Ecological resources exposed to oil pollution using a data-process model. Regional scale risk assessment was done using the combination of geospatial and statistical approaches. Hotspot and Proximity analysis were used for geospatial analysis while weight of evidence was adopted for statistical computation. Ecological resources were identified from land cover maps and ranked according to their perceived importance. Hotspots of oil spill incidents were determined using spatial autocorrelation. Ecological resource vulnerability was determined using buffer zoning of 5 km and 10 km respectively as high and low risk zones, with sample maps made to show extents of resources at risk. Areal extent of ecological resources at risk were calculated and standardized for each of the delineated buffer zones. An aggregate of the weight of each ecological resources and area was computed to categorize the risk as either high, medium or low. This study has successfully assembled and produced relevant spatial and attribute data sets and applied integrated geostatistical analytical techniques to understand the distribution and impacts of oil spills in the Niger Delta. The procedure was seen as an alternative to existing management processes used for monitoring and management of oil spill events.

WARE: Wet AMD Risk-Evaluation Tool as a Clinical Decision-Support System Integrating Genetic and Non-Genetic Factors.

Given the multifactorial features characterizing age-related macular degeneration (AMD), the availability of a tool able to provide the individual risk profile is extremely helpful for personalizing the follow-up and treatment protocols of patients. To this purpose, we developed an open-source computational tool named WARE (Wet AMD Risk Evaluation), able to assess the individual risk profile for wet AMD based on genetic and non-genetic factors. In particular, the tool uses genetic risk measures normalized for their relative frequencies in the general population and disease prevalence. WARE is characterized by a user-friendly web page interface that is intended to assist clinicians in reporting risk assessment upon patient evaluation. When using the tool, plots of population risk distribution highlight a “low-risk zone” and a “high-risk zone” into which subjects can fall depending on their risk-assessment result. WARE represents a reliable population-specific computational system for wet AMD risk evaluation that can be exploited to promote preventive actions and personalized medicine approach for affected patients or at-risk individuals. This tool can be suitable to compute the disease risk adjusted to different populations considering their specific genetic factors and related frequencies, non-genetic factors, and the disease prevalence.

A novel smartphone app for blood pressure measurement: a proof-of-concept study against an arterial catheter

Smartphones may provide a highly available access to simplified hypertension screening in environments with limited health care resources. Most studies involving smartphone blood pressure (BP) apps have focused on validation in static conditions without taking into account intraindividual BP variations. We report here the first experimental evidence of smartphone-derived BP estimation compared to an arterial catheter in a highly dynamic context such as induction of general anesthesia. We tested a smartphone app (OptiBP) on 121 patients requiring general anesthesia and invasive BP monitoring. For each patient, ten 1-min segments aligned in time with ten smartphone recordings were extracted from the continuous invasive BP. A total of 1152 recordings from 119 patients were analyzed. After exclusion of 2 subjects and rejection of 565 recordings due to BP estimation not generated by the app, we retained 565 recordings from 109 patients (acceptance rate 51.1%). Concordance rate (CR) and angular CR demonstrated values of more than 90% for systolic (SBP), diastolic (DBP) and mean (MBP) BP. Error grid analysis showed that 98% of measurement pairs were in no- or low-risk zones for SBP and MBP, of which more than 89% in the no-risk zone. Evaluation of accuracy and precision [bias ± standard deviation (95% limits of agreement)] between the app and the invasive BP was 0.0 ± 7.5 mmHg [− 14.9, 14.8], 0.1 ± 2.9 mmHg [− 5.5, 5.7], and 0.1 ± 4.2 mmHg [− 8.3, 8.4] for SBP, DBP and MBP respectively. To the best of our knowledge, this is the first time a smartphone app was compared to an invasive BP reference. Its trending ability was investigated in highly dynamic conditions, demonstrating high concordance and accuracy. Our study could lead the way for mobile devices to leverage the measurement of BP and management of hypertension.

Oil Spill Environmental Risk Assessment and Mapping in Coastal China Using Automatic Identification System (AIS) Data

The rapid expansion in shipping traffic, oil tankers, and oil field exploration in coastal and marine areas has, inevitably, resulted in the occurrence of many oil spill accidents. Oil spill accidents, which cause serious socio-economic, health, and environmental risks in coastal and marine areas, are a global concern. An oil spill pollution risk distribution map, combining multiple spill sources, is an effective tool by which to identify high-risk areas, which may help decision-makers in adopting contingency response and integrated coastal management. However, the assessment of oil spill distribution and risk assessment has been restricted, due to their heavy dependence on laboratory experiments and model simulations lacking reliable shipping data, which often derive inaccurate mapping results. This study combines the automatic identification system (AIS) and other data to precisely quantify the spatial extent of accident risk in coastal China. Based on oil quantity, oil spill rate, and accident probability, the ship, oil storage tank, submarine pipeline, and oil platform accidents spill risk index is analyzed. Next, combined with the sensitive degree of a coastal area, considering environmental and social issues, the oil spill environmental risk index is calculated. The oil spill pollution risk level is classified into five categories based on the oil spill pollution risk index, namely the low-risk zone, relatively low-risk zone, moderate-risk zone, relatively high-risk zone, and high-risk zone. The relatively high oil spill environmental risk concentration zone is located in the Bohai Sea, inter-border area between the Yellow Sea and Bohai Sea, the Yangtze River estuary, south of the Taiwan Strait, and the Pearl River estuary. The high-risk zone in the Bohai Sea is 36,018 km2 in area, with an average risk value of 32.23, whereas the high-risk area in the Pearl River estuary is only 14,007 km2. The high-risk area proportions in Tianjin are 23.5%, while those in Fujian, Hainan, Jiangsu, and Guangxi are very low. The low-risk area proportion in Hainan Province is 62%, while the value in Tianjin is only 2.9%. This study will be helpful in assisting decision-makers in mapping the influence area of oil spills and adopting the important strategies and effective management and conservation countermeasures for ship accidents in the coastal areas of China.

Benggang (collapsing hill) erosion hazard zoning based on the minimum cumulative resistance model: A case study of a small watershed in Anxi County, Fujian, China

In order to understand the possibility and spatial pattern of Benggang (collapsing hill) erosion in risk assessment and distinguish the primary and secondary areas in Benggang prevention, we took a small watershed in Anxi County (Fujian, China) as the study area and Benggang as the source, and constructed the Benggang expansion resistance surface using the minimum cumulative resistance (MCR) model and divided the risk zoning. The results showed that the area around Benggang displayed a low resistance value, while the northwest and southeast areas displayed a high resistance value. The Benggang expansion resistance surface had an island type form. Based on resistance surface, the research region was divided into very high-risk, high-risk, medium risk, low-risk and very low-risk zones. We proposed corresponding Benggang management suggestions for those zones. A total of 21 strategic saddle points were extracted based on the resistance surface morphology. The strategic points in the lower safety zone were considered as the priority areas for Benggang prevention. We compared the hazard results based on the MCR model and the information quantity method. These results were consistent in spatial distribution, indicating the reliability of the results of hazard zoning by the MCR model.

Assessing the Spatial Mapping of Heat Vulnerability under Urban Heat Island (UHI) Effect in the Dhaka Metropolitan Area

The urban heat island (UHI) phenomenon gets intensified in the process of urbanization, which increases the vulnerability of urban dwellers to heatwaves. The UHI-induced vulnerability to heatwaves has increased in Bangladesh during past decades. Thus, this study aims to examine the UHI and vulnerability to heatwaves in the city of Dhaka using a heat vulnerability index (HVI). The HVI is constructed using various demographic, socioeconomic, and environmental risk variables at thana level. Principal component analysis (PCA) was applied to the 26 normalized variables for each of the 41 thanas of Dhaka to prepare the HVI. Result shows that more than 60% of the city is under built-up areas, while vegetation cover and water bodies are in low proportion. Analysis of HVI shows that the very high- and high-risk zones comprise 6 and 11 thanas, while low- and very low-risk zones comprise only 5 and 8 thanas. The correlation of HVI with variables such as exposure (0.62) and sensitivity (0.80) was found to be highly positive, while adaptive capacity had a negative correlation (−0.26) with the HVI. Findings of this study can be utilized in the mitigation of UHI phenomenon and maintaining the thermal comfort of Dhaka.