scholarly journals Comparative Evaluation of Various Statistical Models and Its Accuracy for Landslide Risk Mapping: A Case Study on Part of Himalayan Region, India

2020 ◽  
Author(s):  
C. Prakasam ◽  
Aravinth R. ◽  
Varinder S. Kanwar ◽  
B. Nagarajan
Keyword(s):  
Statistical Models ◽  
Himachal Pradesh ◽  
Low Risk ◽  
Process Models ◽  
Landslide Risk ◽  
Risk Category ◽  
Contributing Factors ◽  
Risk Areas ◽  
Risk Zones ◽  
Gis Environment

Among other natural hazards, Landslides are the most prominent and frequently occurring natural disaster in the state of Himachal Pradesh with higher socio-economical losses. About 0.42 million sq.kms of area are prone to landslide activities in our country that is excluding the snow covered areas. The current research focuses on estimating the landslide risk zones of the Shimla Tehsil, Himachal Pradesh using various statistical models. Landslide contributing factors as such Landuse Landcover, Elevation, Slope, Lithology, Soil, Geology and Geomorphology has been used to assess the Landslide risk factors. Data obtained from LANDSAT 8 OLI sensors, SRTM DEM, Soil and Land Use Survey of India and SOI Toposheets have been used as sources. Weighted Overlay, Fuzzy logic and Analytical Hierarchical Process models will be used to categorize the Vulnerability and risk Zones of the study area. The causative factors were analyzed and processed in GIS environment. These values will be then being integrated using various studied models to produce individual landslide vulnerability and risk zones. The results reveal that most of the study area falls under Very Low risk category with a total coverage of 67.34%. Low and Moderate area covers about 23% and 9.13% of the study area. Higher risk areas only account for about 0.46%. Higher percent of the study area is mostly covered by settlements. National highways, Metal roads, Slopes and Denser settlements are located along the Moderate and low risk areas. The results retrieved from the WOM model reveals a total of 55% of the area comes under very low category. Low and Moderate category covers about 31.4% and 10.6% of the study area. High and Very High category cover a total of 1.9% together.

scholarly journals Spatial Landslide Risk Assessment at Phuentsholing, Bhutan

Geosciences ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 131 ◽  
Author(s):  
Abhirup Dikshit ◽  
Raju Sarkar ◽  
Biswajeet Pradhan ◽  
Saroj Acharya ◽  
Abdullah M. Alamri
Keyword(s):  
Field Study ◽  
Landslide Risk ◽  
Infrastructure Development ◽  
Contributing Factors ◽  
Study Region ◽  
Landslide Occurrence ◽  
Spatial Probability ◽  
Gis Environment ◽  
Combination Approach ◽  
Landslide Hazard Map

Landslides are one of the most destructive and most recurring natural calamities in the Himalayan region. Their occurrence leads to immense damage to infrastructure and loss of land, human lives, and livestock. One of the most affected regions is the Bhutan Himalayas, where the majority of the landslides are rainfall-induced. The present study aims to determine the hazard and risk associated with rainfall-induced landslides for the Phuentsholing region located in the southwestern part of the Bhutan Himalayas. The work involves developing a landslide risk map using hazard and vulnerability maps utilizing landslide records from 2004 to 2014. The landslide hazard map was generated by determining spatial and temporal probabilities for the study region. The spatial probability was computed by analyzing the landslide contributing factors like geology, slope, elevation, rainfall, and vegetation based on comprehensive field study and expertise about the area. The contributing factors were divided into various classes and the percentage of landslide occurrence under each class was calculated to understand its contributing significance. Thereafter, a weighted linear combination approach was used in a GIS environment to develop the spatial probability map which was multiplied with temporal probabilities based on regional rainfall thresholds already determined for the region. Consequently, vulnerability assessment was conducted using key elements at risk (population, land use/land cover, proximity to road, proximity to stream) and the weights were provided based on expert judgment and comprehensive field study. Finally, risk was determined and the various regions in the study area were categorized as high, medium, and low risk. Such a study is necessary for low-economic countries like Bhutan which suffers from unavailability of extensive data and research. The study is conducted for a specific region but can be extended to other areas around the investigated area. The tool can serve as an indicator for the civil authorities to analyze the risk posed by landslides due to the rapid infrastructure development in the region.

scholarly journals Delineating Drought Risk Areas Using Remote Sensing and Geographic Information Systems– A Case Study of Western Highlands Province, Papua New Guinea

2018 ◽  
Vol 3 (10) ◽  
pp. 103-110
Author(s):  
Nicholas Korada ◽  
Tingneyuc Sekac ◽  
Sujoy Kumar Jana ◽  
Dilip Kumar Pal
Keyword(s):  
Remote Sensing ◽  
Papua New Guinea ◽  
New Guinea ◽  
Drought Risk ◽  
Gis And Remote Sensing ◽  
Multi Criteria Evaluation ◽  
Risk Areas ◽  
Basic Services ◽  
Risk Zones ◽  
Gis Environment

In the highlands of Papua New Guinea, rain-fed subsistence farming has been the main source of food and small cash earnings for the majority of the rural population. Consequently, as a result of elongated period of drought, reduction in food and water supply bring forth starvation / malnutrition led sickness and death, especially when authorities fail to intervene because inaccessibility and  remoteness of the highly dissected terrain, as a result relief and basic services don’t reach the hungry mouth on time. Such conditions were reported recently in many parts of Papua New Guinea especially prevalent in coastal regions and uplands of the highlands region. In this study, GIS and Remote Sensing (RS) technology were employed in highlighting and demarcating potential drought risk zones in Western Highlands Province. Basically, several environmental factors like; soil types, NDVI, rainfall, terrain, population demography and surface temperature were prepared and integrated in GIS environment through multi-criteria evaluation techniques where risk areas were identified. The final output generated from factors integration were then assessed and reclassified to indicate levels of drought risk zones from Low, Medium and High. Hence, several built-up areas where then marked on each risk zones in an attempt to highlight the location, distribution and accessibility in respect to the risk areas identified.

scholarly journals Application of Geographic Information Systems for Flood Risk Analysis: A Case Study from Accra Metropolitan Area

2019 ◽  
Vol 13 (1) ◽  
pp. 81-97
Author(s):  
Alex Barimah Owusu ◽  
Mathias Agbozo
Keyword(s):  
Flood Risk ◽  
Drainage Density ◽  
Low Risk ◽  
Soil Drainage ◽  
Risk Area ◽  
The Public ◽  
Risk Areas ◽  
Risk Zones ◽  
High Flood

Abstract The main objective of the study was to identify high flood risk zones in AMA. The study also used questionnaires to assess local knowledge on what accounts for the high flood risk in their community. Spatial analysis techniques were used to model flood risk based on the following contributory factors; land cover, soil, drainage density, topography and proximity to rivers. The results show that high flood risk areas covered 46.3km2(20%), moderate risk area, 72.9km2(31.6%), low risk area 41.5km2(18%) and very low risk areas, about 6.7km2(2.9%). The high flood risk zones were low-lying areas below 50 meters above sea level and closely associated with poor drainage systems. People perceived not just low-lying areas as a paramount reason accounting for flooding but also very bad waste disposal habit of the public. These offsets the efforts of waste management companies to keep drains free of refuse.

scholarly journals Multidimensional dynamic healthcare personnel (HCP)-centric model from a low-income and middle-income country to support and protect COVID-19 warriors: a large prospective cohort study

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e043837
Author(s):  
Usha Dutta ◽  
Anurag Sachan ◽  
Madhumita Premkumar ◽  
Tulika Gupta ◽  
Swapnajeet Sahoo ◽  
...  
Keyword(s):  
High Risk ◽  
Low Income ◽  
Tertiary Care ◽  
Low Risk ◽  
Transmission Risk ◽  
Healthcare Personnel ◽  
Risk Zone ◽  
Increased Risk ◽  
Medium Risk ◽  
Risk Zones

ObjectivesHealthcare personnel (HCP) are at an increased risk of acquiring COVID-19 infection especially in resource-restricted healthcare settings, and return to homes unfit for self-isolation, making them apprehensive about COVID-19 duty and transmission risk to their families. We aimed at implementing a novel multidimensional HCP-centric evidence-based, dynamic policy with the objectives to reduce risk of HCP infection, ensure welfare and safety of the HCP and to improve willingness to accept and return to duty.SettingOur tertiary care university hospital, with 12 600 HCP, was divided into high-risk, medium-risk and low-risk zones. In the high-risk and medium-risk zones, we organised training, logistic support, postduty HCP welfare and collected feedback, and sent them home after they tested negative for COVID-19. We supervised use of appropriate personal protective equipment (PPE) and kept communication paperless.ParticipantsWe recruited willing low-risk HCP, aged <50 years, with no comorbidities to work in COVID-19 zones. Social distancing, hand hygiene and universal masking were advocated in the low-risk zone.ResultsBetween 31 March and 20 July 2020, we clinically screened 5553 outpatients, of whom 3012 (54.2%) were COVID-19 suspects managed in the medium-risk zone. Among them, 346 (11.4%) tested COVID-19 positive (57.2% male) and were managed in the high-risk zone with 19 (5.4%) deaths. One (0.08%) of the 1224 HCP in high-risk zone, 6 (0.62%) of 960 HCP in medium-risk zone and 23 (0.18%) of the 12 600 HCP in the low-risk zone tested positive at the end of shift. All the 30 COVID-19-positive HCP have since recovered. This HCP-centric policy resulted in low transmission rates (<1%), ensured satisfaction with training (92%), PPE (90.8%), medical and psychosocial support (79%) and improved acceptance of COVID-19 duty with 54.7% volunteering for re-deployment.ConclusionA multidimensional HCP-centric policy was effective in ensuring safety, satisfaction and welfare of HCP in a resource-poor setting and resulted in a willing workforce to fight the pandemic.

scholarly journals Water erosion vulnerability and sediment delivery rate in upper Iguaçu river basin – Paraná

RBRH ◽  
2016 ◽  
Vol 21 (4) ◽  
pp. 728-741 ◽  
Author(s):  
Matheus Fonseca Durães ◽  
José Alexandre Pinto Coelho Filho ◽  
Vinícius Augusto de Oliveira
Keyword(s):  
Land Use ◽  
River Basin ◽  
Water Erosion ◽  
Sustainable Land Use ◽  
Delivery Rate ◽  
Sediment Delivery ◽  
Solid Discharge ◽  
Risk Areas ◽  
Gis Environment ◽  
Iguaçu River

ABSTRACT Soil erosion is one of the most striking environmental degradation processes, which its mapping and assessment is an important tool for management activities and natural resource management in river basins, allowing managers to implement policies and sustainable land use occupation. This work aimed to apply the Revised Universal Soil Loss Equation (RUSLE) in a GIS environment in the upper Iguaçu river basin, located at Paraná State, in order to assess the vulnerability to water erosion as well as the concentration of dissolved solids in suspension to estimate the solid discharge and sediment delivery rate, allowing the identification of more susceptible areas to water erosion. The results showed that over 23.52% of the upper Iguaçu river basin presented soil losses below 2.5 t ha–1 yr–1, meaning current low potential for erosion. Regarding the solid discharge, the basin has values ranging from low to very high, also leading to high values for sediment delivery rate. The identification of risk areas associated with accelerated erosion, carried out in this study provide important information for measures associated with the management, conservation and planning of land use in the basin, which is highly relevant for predicting development of various scenarios for the state Paraná for its hydroelectric potential.

scholarly journals Spatial-time Visualization of Cutaneous Leishmaniasis in an Urban Area: Informing Health Policy and Practice

2020 ◽  
Author(s):  
Neda Firouraghi ◽  
Sayyed Mostafa Mostafavi ◽  
Amene Raouf-Rahmati ◽  
Alireza Mohammadi ◽  
Reza Saemi ◽  
...  
Keyword(s):  
High Risk ◽  
Incidence Rate ◽  
Urban Area ◽  
Incidence Rates ◽  
Low Risk ◽  
Health Concern ◽  
Surveillance Systems ◽  
Cross Sectional ◽  
Targeted Interventions ◽  
Risk Areas

Abstract Background:Cutaneous leishmaniasis (CL) is an important public health concern worldwide. Iran is among the most CL-affected countries, being listed as one of the first six endemic countries in the world. In order to develop targeted interventions, we performed a spatial-time visualization of CL cases in an urban area to identify high-risk and low-risk areas during 2016-2019.Methods:This cross-sectional study was conducted in the city of Mashhad. Patient data were gathered from Mashhad health centers. All cases (n=2425) were diagnosed in two stages; the initial diagnosis was based on clinical findings. Subsequently, clinical manifestation was confirmed by parasitological tests. The data were aggregated at the neighborhood and district levels and smoothed CL incidence rates per 100,000 individuals were calculated using the spatial empirical Bayesian approach. Furthermore, we used the Anselin Local Moran’s I statistic to identify clusters and outliers of CL distribution during 2016-2019 in Mashhad. Results:The overall incidence rates decreased from 34.6 per 100,000 in 2016 to 19.9 per 100,000 individuals in 2019. Both cluster analyses by crude incidence rate and smoothed incidence rate identified high-risk areas in southwestern Mashhad over the study period. Furthermore, the analyses revealed low-risk areas in northeastern Mashhad over the same 3-year period.Conclusions:The southwestern area of Mashhad had the highest CL incidence rates. This piece of information might be of value to design tailored interventions such as running effective resource allocation models, informed control plans and implementation of efficient surveillance systems. Furthermore, this study generates new hypotheses to test potential relationships between socio-economic and environmental risk factors and incidence of CL in areas with higher associated risks.

scholarly journals Assessment of risk of developing diabetes using Indian diabetes risk score in the urban field practice area of Rajarajeswari Medical College and Hospital, Bangalore

2019 ◽  
Vol 7 (1) ◽  
pp. 170
Author(s):  
Nazia N. Shaik ◽  
Swapna M. Jaswanth ◽  
Shashikala Manjunatha
Keyword(s):  
At Risk ◽  
High Risk ◽  
Risk Score ◽  
Diabetes Risk ◽  
Low Risk ◽  
Risk Category ◽  
Moderate Risk ◽  
Medical College ◽  
Field Practice ◽  
Diabetes Risk Score

Background: Diabetes is one of the largest global health emergencies of the 21st century. As per International Federation of Diabetes some 425 million people worldwide are estimated to have diabetes. The prevalence is higher in urban versus rural (10.2% vs 6.9%). India had 72.9 million people living with diabetes of which, 57.9% remained undiagnosed as per the 2017 data. The objectives of the present study were to identify subjects who at risk of developing Diabetes by using Indian diabetes risk score (IDRS) in the Urban field practice area of Rajarajeswari Medical College and Hospital (RRMCH).Methods: A cross sectional study was conducted using a Standard questionnaire of IDRS on 150 individuals aged ≥20 years residing in the Urban field practice area of RRMCH. The subjects with score <30, 30-50, >or =60 were categorized as having low risk, moderate risk and high risk for developing diabetes type-2 respectively.Results: Out of total 150 participants, 36 (24%) were in high-risk category (IDRS≥60), the majority of participants 61 (41%) were in the moderate-risk category (IDRS 30–50) and 53 (35%) participants were found to be at low-risk (<30) for diabetes. Statistical significant asssociation was found between IDRS and gender, literacy status, body mass index (p<0.0000l).Conclusions: It is essential to implement IDRS which is a simple tool for identifying subjects who are at risk for developing diabetes so that proper intervention can be carried out at the earliest to reduce the burden of diabetes.

scholarly journals Global trends in nasopharyngeal cancer mortality since 1970 and predictions for 2020: Focus on low-risk areas

2017 ◽  
Vol 140 (10) ◽  
pp. 2256-2264 ◽  
Author(s):  
Greta Carioli ◽  
Eva Negri ◽  
Daisuke Kawakita ◽  
Werner Garavello ◽  
Carlo La Vecchia ◽  
...  
Keyword(s):  
Cancer Mortality ◽  
Nasopharyngeal Cancer ◽  
Low Risk ◽  
Global Trends ◽  
Risk Areas

Abstract 187: Cardiac Arrest Incidence, Bystander Cardiopulmonary Resuscitation Rates, and Community Characteristics Differ by High and Low Risk Areas

Circulation ◽  
2019 ◽  
Vol 140 (Suppl_2) ◽  
Author(s):  
Rebecca Cash ◽  
Madison K Rivard ◽  
Eric Cortez ◽  
David Keseg ◽  
Ashish Panchal
Keyword(s):  
Cardiac Arrest ◽  
High Risk ◽  
Cardiopulmonary Resuscitation ◽  
Low Risk ◽  
Poverty Level ◽  
Community Characteristics ◽  
Franklin County ◽  
Census Tracts ◽  
Bystander Cardiopulmonary Resuscitation ◽  
Risk Areas

Introduction: Survival from out-of-hospital cardiac arrest (OHCA) has significant variation which may be due to differing rates of bystander cardiopulmonary resuscitation (BCPR). Defining and understanding the community characteristics of high-risk areas (census tracts with low BCPR rates and high OHCA incidence) can help inform novel interventions to improve outcomes. Our objectives were to identify high and low risk census tracts in Franklin County, Ohio and to compare the OHCA incidence, BCPR rates, and community characteristics. Methods: This was a cross-sectional analysis of OHCA events treated by Columbus Division of Fire in Franklin County, Ohio from the Cardiac Arrest Registry to Enhance Survival between 1/1/2010-12/31/2017. Included cases were 18 and older, with a cardiac etiology OHCA in a non-healthcare setting, with EMS resuscitation attempted. After geocoding to census tracts, Local Moran’s I and quartiles were used to determine clustering in high risk areas based on spatial Empirical Bayes smoothed rates. Community characteristics, from the 2014 American Community Survey, were compared between high and low risk areas. Results: From the 3,841 included OHCA cases, the mean adjusted OHCA incidence per census tract was 0.67 per 1,000 with a mean adjusted BCPR rate of 31% and mean adjusted survival to discharge of 9.4%. In the 25 census tracts identified as high-risk areas, there were significant differences in characteristics compared to low-risk areas, including a higher proportion of African Americans (64% vs. 21%, p<0.001), lower median household income ($30,948 vs. $54,388, p<0.001), and a higher proportion living below the poverty level (36% vs. 20%, p<0.001). There was a 3-fold increase in the adjusted OHCA incidence between high and low risk areas (1.68 vs. 0.57 per 1,000, p<0.001) with BCPR rates of 27% and 31% (p=0.31), respectively. Compared to a previous analysis, 9 (36%) census tracts persisted as high-risk but an additional 16 were newly identified. Conclusions: Neighborhood-level variations in OHCA incidence are dramatic with marked disparities in characteristics between high and low risk areas. It is possible that improving OHCA outcomes requires multifaceted interventions to address social determinants of health.

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