scholarly journals AHP and GIS-based Risk Zonation of COVID-19 in North East India

2020 ◽  
Vol 15 (3) ◽  
pp. 640-652
Author(s):  
Ranjit Mahato ◽  
Dhoni Bushi ◽  
Gibji Nimasow
Keyword(s):  
Health Workers ◽  
Poverty Line ◽  
Controlling Factors ◽  
Health Facilities ◽  
Geographical Information ◽  
Risk Zone ◽  
North East India ◽  
North East ◽  
Risk Zonation ◽  
Risk Zones

On 31st December 2019, a novel virus was reported from Wuhan City of Hubei Province of China, and later it was recognized as SARS-COV-2 (COVID-19). As the virus is highly human to human contagious, it has spread worldwide within a very short time. Since 24th March 2020, after the first reported case in North East India, the total confirmed cases reached up to 4,633 on 11th June 2020. In this work, an attempt has been made to delineate risk zones of COVID-19 in North East India using the Analytic Hierarchy Process (AHP) and overlay analysis in Geographical Information System (GIS). The evaluation is based on 14 criteria that were classified into promoting and controlling factors. The promoting factors include population size, population density, urban population, elderly population, population below the national poverty line, and percentage of marginal workers. In contrast, the controlling factors include available doctors, other health workers, public health facilities, available beds, governance index (composite and health), and testing laboratories. The results were classified into very high, high, moderate, low, and very low risk zones. Most densely populated states with massive pressure on health facilities are likely to have a higher risk of COVID-19. Assam, Tripura, Meghalaya, and Nagaland show a high COVID-19 risk, which constitutes almost 76.93% of the North East India population, covering 48.80% of surface area. The states under a moderate risk zone include 6.92% of the population over 8.52% of the area. Lastly, 16.15% of the people living over 42.69% of the total area belong to the states with a lower risk zone.

scholarly journals Landslide hazard and risk zonation of Thankot – Chalnakhel area,

1970 ◽  
Vol 31 ◽  
pp. 43-50 ◽  
Author(s):  
Pradeep Paudyal ◽  
Megh Raj Dhital
Keyword(s):  
Landslide Hazard ◽  
Geographical Information ◽  
Hazard Map ◽  
Risk Map ◽  
Risk Zonation ◽  
Hazard Zone ◽  
Risk Zones ◽  
Vulnerability Map ◽  
Landslide Hazard Map ◽  
Moderate Hazard

The rocks in the Thankot–Chalnakhel area constitute the Chandragiri Range bordering the Kathmandu valley. The Phulchauki Group of rocks comprise its steep and rugged south slope, whereas the gentle north slope is covered by fluvio-lacustrine deposits of the Kathmandu basin with some recent alluvial fans. During the field study, 94 landslides (covering about 0.24 sq km) were mapped. Most of them were triggered by intense rainfall within the last two years. Landslides are generally found on steep colluvial slope (25°–35°) and dry cultivated land. Based on a computer-based geographical information system, a landslide hazard map, a vulnerability map, and a risk map were prepared. The landslide hazard map shows 20% of the area under high hazard zone, 41% under moderate hazard zone, and 39% under low hazard zone. The risk map generated by combining the hazard map and vulnerability map shows 19% of the area under high and very high risk zones, 33% under moderate risk zone, and 48% under low and very low risk zones.

scholarly journals Wildfire Risk Zonation of Sudurpaschim Province, Nepal

2020 ◽  
Vol 17 ◽  
pp. 155-173
Author(s):  
Bikram Singh ◽  
Menuka Maharjan ◽  
Mahendra Singh Thapa
Keyword(s):  
Deciduous Forest ◽  
Temporal Distribution ◽  
Fire Risk ◽  
Moderate Risk ◽  
Wildfire Management ◽  
Risk Zone ◽  
Wildfire Risk ◽  
Risk Zonation ◽  
Risk Zones ◽  
Physiographic Regions

Wildfire is one of the major destructive hazards which have significant effect on environment, society, and economy. However, limited studies have been carried out on spatial and temporal distribution of wildfire, especially in developing countries like Nepal. The objective of this study was to assess wildfire risk zonation of Sudurpaschim province of Nepal by applying Remote Sensing and GIS. Sudurpaschim province has been divided into four fire risk zones i.e., high, moderate, low and no risk zone. In Sudurpaschim province, about 30.84% area falls under high fire risk zone followed by moderate risk (58.30%), low risk (10.13%) and no risk (0.72%). Among five physiographic regions, Siwalik region is more susceptible to fire due to various factors, such as deciduous forest, topography, terrain, etc. From 2012 to 2019, about 44,342 fire incidences were reported in this province. Approximately 88% wildfire was recorded in spring, the season being dry. Overall, geographically Siwalik region and temporarily spring season should be in high priority for developing and implementing wildfire management activities in Sudurpaschim province.

scholarly journals Mapping the Forest Fire Risk Zones Using Artificial Intelligence with Risk Factors Data

2022 ◽  
Author(s):  
Volkan Sevinc
Keyword(s):  
Artificial Intelligence ◽  
High Risk ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
Geographical Information ◽  
Data Set ◽  
Risk Zone ◽  
Risk Zones ◽  
Forest Fire Risk

Abstract 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 nine human-induced factors, three natural factors, and a temperature factor causing forest fires. Moreover, an artificial intelligence method, k-means, clustering algorithm was employed in preparation of the fire risk zone map. Turkey was selected as the study area as there are social and economic varieties among its zones. Therefore, the forestry zones in Turkey were separated into three groups as low, moderate, and high-risk categories and a map was provided for these risk zones. The map reveals that the forestry zones on the west coast of Turkey are under high risk of forest fire while the moderate risk zones mostly exist in the southeastern zones. The zones located in the interior parts, in the east, and on the north coast of Turkey have comparatively lower forest fire risks.

Prevalence and determinants of oral potentially malignant lesions using mobile health in a rural block, northeast India

2021 ◽  
pp. 004947552110499
Author(s):  
Rohan Michael Ramesh ◽  
Sanjana Patrick ◽  
Zubemo Lotha ◽  
Azole ◽  
Atsung Aier ◽  
...  
Keyword(s):  
Health Workers ◽  
Northeast India ◽  
Predictive Values ◽  
Logistic Regression Models ◽  
North East India ◽  
North East ◽  
Recommended Treatment ◽  
Potentially Malignant ◽  
Malignant Lesions ◽  
Sensitivity Specificity

In a rural block in North East India, community health workers (CHW) empowered with a mobile phone-based application screened a total of 2,686 participants for Oral Potentially Malignant Lesions (OPMLs), and an oral medicine specialist recommended treatment remotely. Independent risk factors were determined using independent multiple logistic regression models. Nearly 700 (26%) participants were identified with OPMLs. The sensitivity, specificity, positive predictive values, negative predictive values and accuracy of the CHW was 70.3, 88.4, 66.8, 89.9% and 83.7% respectively. Male gender, married status, smokeless tobacco, paan, areca-nut and alcohol consumption were independent predictors of OPMLs, the burden of which in North East India can be attributed to the high consumption of tobacco and non-tobacco products. Such programmes, with the recommendations from remote specialists, will facilitate early detection in remote settings.

scholarly journals Generating Self-Employment Opportunities in North-East India: Challenges Faced by the Self-Help Groups

2018 ◽  
Vol 7 (2) ◽  
pp. 12-18
Author(s):  
Pradeep Kumar Chakravarty
Keyword(s):  
Urban Areas ◽  
Urban Poverty ◽  
Poverty Line ◽  
North East India ◽  
Cascading Effect ◽  
North East ◽  
The North ◽  
Self Help ◽  
The Government ◽  
Self Help Groups

The Government has put in place policies and programmes to alleviate urban poverty. Urban Local Bodies (ULBs) are the facilitators to reduce poverty in their respective areas. Urban Self-Help Groups (SHGs) aim at sustainable employment for their members. But they face many challenges during their day-to-day activities. The present study aims at identifying the issues, challenges or problems faced by SHGs in the urban areas of the State of Tripura. It relates to urban areas of Tripura, a small hilly state in the North-East India, for which 14 ULBs out of 20 have been selected from all the eight districts. Based on a sample size of 353 SHGs, the study shows that women SHG members have to face internal or organizational challenges and external ones in running SHGs having a cascading effect to their income level, which is not sufficient enough to cross the poverty line sustainably. The paper has also recommended certain solutions to the problems.

Past Verses Present; Metamorphosis in Different Spheres of Guwahati: A Study of Srutimala Duara’s Mindprints of Guwahati

2020 ◽  
Vol 8 (2) ◽  
pp. 13
Author(s):  
Ankita Pandey
Keyword(s):  
Point Of View ◽  
Areca Nut ◽  
Medieval Period ◽  
River Bank ◽  
North East India ◽  
North East ◽  
The North ◽  
Indian State ◽  
The City ◽  
Beautiful City

Guwahati derives its name from the Assamese word “Guwa” means areca nut and “Haat” means market. However, the modern Guwahati had been known as the ancient Pragjyotishpura and was the capital of Assam under the Kamrupa kingdom. A beautiful city Guwahati is situated on the south bank of the river Bramhaputra. Moreover, It is known as the largest city in the Indian state of Assam and also the largest metropolis in North East India. It has also its importance as the gateway to the North- East India. Assamese and English are the spoken languages in Guwahati.  In 1667, the Mogul forces were defeated in the battle by the Ahom forces commanded by Lachut Barphukan. Thus, in a sense Guwahati became the bone of contention among the Ahoms, Kochas and the Moguls during the medieval period.  Guwahati the administrative headquarters of Lower Assam with a viceroy or Barbhukan was made by the Ahom king.  Since 1972 it has been the capital of Assam. The present paper will discuss the changes happened in Guwahati over the period of late 1970s till the present time. It will focus on the behavior of people, transformed temples, Panbazar of the city, river bank of Bramhaputra, old Fancy Bazaar, chaotic ways, festivals and seasons including a fifth man made season etc. It will also deal how over the years a city endowed with nature’s gifts and scenic views, has been changing as “a dirty city”. Furthermore, it will also present the insurgencies that have barged into the city. The occurrence of changes will be discussed through the perspective and point of view of Srutimala Duara as presented in her book Mindprints of Guwahati.

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