Bipin AcharyaNepal Open University
Bipin Acharya
PhD (Remote Sensing and GIS)
Looking for postdoctoral/researcher opportunity in the field of geohealth and spatial epidemiology
About
39
Publications
39,128
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Introduction
Medical/Health Geographer interested in infectious disease research based on geographical approach using high tech GIS and Remote Sensing technology.
Additional affiliations
September 2018 - April 2021
Position
- Research Associate
Description
- Medical/Health Geographer working in the field infectious disease research based on geographical approach using high tech GIS and Remote Sensing technology.
September 2014 - June 2018
Education
June 2016 - June 2016
September 2014 - June 2018
February 2012 - February 2012
George Mason University Smithsonian Conservation Biology Institute Smithsonian-Mason School of Conservation
Field of study
- Spatial Ecology, Geospatial Analysis and Remote Sensing for Conservation
Publications
Publications (39)
The rapid increase in urbanization due to population growth leads to the degradation of vegetation in major cities. This study investigated the spatial patterns of the ecoenvironmental conditions of inhabitants of two distinct Asian capital cities, Beijing of China and Islamabad of Pakistan, by utilizing Earth observation data products. The signifi...
Background
Due to recent emergence, dengue is becoming one of the major public health problems in Nepal. The numbers of reported dengue cases in general and the area with reported dengue cases are both continuously increasing in recent years. However, spatiotemporal patterns and clusters of dengue have not been investigated yet. This study aims to...
Both the number of cases of dengue fever and the areas of outbreaks within Nepal have increased significantly in recent years. Further expansion and range shift is expected in the future due to global climate change and other associated factors. However, due to limited spatially-explicit research in Nepal, there is poor understanding about the pres...
Increasing trends of urbanization lead to vegetation degradation in big cities and affect the urban thermal environment. This study investigated (1) the cooling effect of urban green space spatial patterns on Land Surface Temperature (LST); (2) how the surrounding environment influences the green space cool islands (GCI), and vice versa. The study...
This study describes spatiotemporal distribution and geospatial diffusion patterns of dengue outbreak of 2013 in Jhapa district, Nepal. Laboratory-confirmed dengue cases were collected from the District Public Health Office, Government of Nepal. Choropleth mapping technique, Global Moran’s Index, SaTScan, and standard deviational ellipse were used...
Background:
Visceral leishmaniasis (VL) is an important re-emerging neglected tropical disease associated with poverty. Despite the elimination initiative started in 2005, VL cases have been expanding into geographic areas in Nepal. The present study aims at exploring the trends of VL from 1980 to 2019.
Methods:
This retrospective analysis cover...
Anemia among under-five children is the major health problem in Nepal. The lack of nutritional supplementation and lack of healthcare facilities are influential factors of anemia. Thus, the main objective of this study is to explore spatial variations and determinants of anemia among under-five children in Nepal. Nepal Demographic and Health Survey...
Background: Psychological problems increased during the period of COVID-19. Lockdown” is adopted in many countries of the world. It has also been seen that COVID-19 has led not only to an increase of infection and death but also vast change in the lifestyles of every individual especially in young adults causing various mental health issues. Howeve...
Nepal has been strongly influenced by the COVID-19 pandemic and struggling to contain it with multiple interventions. We assessed the spatiotemporal dynamics of COVID-19 in the context of various restrictions imposed to contain the disease transmission by employing prospective spatiotemporal analysis with SaTScan statistics. We explored active and...
Background
Ambient fine particulate matter (PM2.5) pollution has been associated with mortality from various diseases, however, its association with under-five mortality rate (U5MR) has remained largely unknown.
Methods
Based on the U5MR data across 2851 counties in Mainland China from 1999 to 2012, we employed approximate Bayesian latent Gaussian...
Gandaki River Basin (GRB) is an important part of the central Himalayan region, which provides habitat for numerous wild species. However, climatic changes are making the habitat in this basin more vulnerable. This paper aims to assess the potential impacts of climate change on the spatial distributions of habitat changes for two vulnerable species...
The novel coronavirus disease 2019 (COVID-19) has been the biggest public health problem of the present world. As the number of people suffering from the pandemic is rising, it is likely to claim more life and worsen the global health and economy. Nepal, one of the developing countries in the south Asia has been strongly influenced by the pandemic...
Background
To investigate the effects of air pollution exposure during pregnancy on the indicators of glucose homeostasis and gestational diabetes mellitus (GDM).
Methods
We conducted a birth cohort study in Foshan, China during 2015–2019. Oral glucose tolerance test (OGTT) was administered to each participant during pregnancy. GDM was defined acc...
The coronavirus disease 2019 (COVID-19), the biggest health problem at present, doesn’t have uniform transmission and severity among the countries and communities therein. Knowledge of community vulnerability to the disease would facilitate interventions aimed at transmission control by efficient deployment of available limited resources. Therefore...
The coronavirus disease 19 (COVID-19), the biggest health problem at present, does not have uniform transmission and severity among the countries and communities therein. Knowledge of community vulnerability to the disease would facilitate interventions aimed at transmission control by the efficient deployment of available limited resources. Theref...
Maternal blood glucose level is associated with fetal growth, therefore, its role in the associations between air pollution and birth weight deserves investigation. We examined the mediation effect of maternal blood glucose on the associations between maternal air pollution exposure and birth weight. A total of 10,904 pregnant women in Foshan, Chin...
Background
Previous research has reported the effects of long-term fine particulate matter (PM2.5) pollution on years of life lost (YLL), but these effects may not represent the full impact. This study aims to estimate potential benefits in life time from adhering to daily ambient PM2.5 concentration standards/guidelines.
Methods
This study evalua...
Anthropogenic activities have driven many wildlife species towards extinction. Among these species, the geographic distributions of many are poorly documented, which can limit the effectiveness of conservation. The critically endangered Chinese pangolin (Manis pentadactyla) is experiencing population decline throughout its range due to land-use cha...
Urban growth is a key indicator of economic development. At the same time, haphazard urban growth creates serious socioeconomic, environmental and urban land management problems. In this context, understanding the process of urban landscape change is important for guiding the sustainable growth of urban areas. This study analyzes the urban land cha...
Background
Ambient fine particulate matter pollution (PM2.5) is one leading cause of disease burden, but no study has quantified the association between daily PM2.5 exposure and life expectancy. We aimed to assess the potential benefits in life expectancy by attaining the daily PM2.5 standards in 72 cities of China during 2013–2016.
Methods and fi...
Objectives:
Prenatal exposure to air pollutant has been associated with congenital heart defect (CHD). However, no study has investigated this effect in pre-pregnancy overweighted women. This study aimed to evaluate gestational exposure to particulate pollutant (PM2.5) and gaseous air pollutants (O3 and NO2) on the risk of CHD, and explore the pot...
Being a globally emerging mite-borne zoonotic disease, scrub typhus is a serious public health concern in Nepal. Mapping environmental suitability and quantifying the human population under risk of the disease is important for prevention and control efforts. In this study, we model and map the environmental suitability of scrub typhus using the eco...
Although ambient air pollution has been consistently associated with morbidity and mortality of stroke, there is limited evidence on whether the control of air pollution would associate with a reduced risk of stroke. The citywide air pollution controlling measures during the 2010 Asian Games in Guangzhou provided such an opportunity to answer this...
Background:
Most studies on the short-term health effects of air pollution have been conducted on a daily time scale, while hourly associations remain unclear.
Methods:
We collected the hourly data of emergency ambulance calls (EACs), ambient air pollution, and meteorological variables from 2014 to 2016 in Luoyang, a central Chinese city in Hena...
Although myopia has been largely ignored among the elderly population, there is an increased risk of myopia with advancing age. Ambient air pollution is one potential contributor to vision impairments, but few epidemiological studies have demonstrated such an association. This cross-sectional survey collected the information of 33,626 subjects aged...
The World Health Organization sets up the Ambient Air Quality Guidelines mainly based on short-term and long-term health effects of air pollution. Previous studies, however, have generally revealed a non-threshold concentration-response relationship between air pollution and health, making it difficult to determine a concentration, below which no o...
Dengue fever is expanding rapidly in many tropical and subtropical countries since the last few decades. However, due to limited research, little is known about the spatial patterns and associated risk factors on a local scale particularly in the newly emerged areas. In this study, we explored spatial patterns and evaluated associated potential env...
Land use and land cover is a fundamental variable that affects many parts of social and physical environmental aspects. Land use and land cover changes (LUCC) has been known as one of the key drivers of affecting in ecosystem services. The trans-boundary Gandaki River Basin (GRB) is the part of Central Himalayas, a tributary of Ganges mega-river ba...
Remotely sensed data are often adversely affected by many types of noise, which influences the classification result. Supervised machine-learning (ML) classifiers such as random forest (RF), support vector machine (SVM), and back-propagation neural network (BPNN) are broadly reported to improve robustness against noise. However, only a few comparat...
Dengue fever is one of the leading public health problems of tropical and subtropical countries across the world. Transmission dynamics of dengue fever is largely affected by meteorological and environmental factors, and its temporal pattern generally peaks in hot-wet periods of the year. Despite this continuously growing problem, the temporal dyna...
City green infrastructure (CGI) makes cities more resilient and sustainable, as required by the United Nations’ (UN) Sustainable Development Goal 11–Sustainable Cities and Communities. Based on the CGI policies of Beijing, land use/land cover (LULC) changes of two Asian capitals, Beijing, China and Islamabad, Pakistan, are simulated. LULC maps for...
Genetic diversity of a species is influenced by multiple factors, including the Quaternary glacial-interglacial cycles and geophysical barriers. Such factors are not yet well documented for fauna from the southern border of the Himalayan region. This study used mitochondrial DNA (mtDNA) sequences and ecological niche modeling (ENM) to explore how t...
Dengue fever has been of one of the major public threats globally. It is being intense in previously endemic region and emerging as a new disease in other regions of the world which were considered safe earlier. First dengue case in Nepal was reported in early 2004. Since then, it has been spreading rapidly with frequent outbreak in the subsequent...
Questions
Questions (10)
How to downloads Global Precipitation Measurement data in R????. Your help will be appreciated
I want to extract Landsat TM/ETM based NDVI value for 1000-point location of China for 10 years (2004-2014) study period. As, these points are distributed in the entire china, downloading the Landsat images and computation of NDVI myself for that point location is much time consuming. Therefore, I am looking some geoportal (or some R scripts) from where I can extract Landsat TM/ETM based NDVI value or can use R script to automatic download images and compute the NDVI. I am looking for your suggestion.
Continuous variables such as elevation, precipitation, temperature, etc. are normally summarized based on zonal statistics such as mean, median standard deviation for the spatial analysis. Then what would be the best method of summarize in the case of categorical data, for example land cover in this case?. Looking forward for you valuable suggestions.
Thanks
Bipin
Which google api root is working currently from mainland china? I tried http://ditu.google.cn/maps/api/geocode and http://maps.google.cn/maps/api/geocode/json but neither is working now.
Is there any differences between spatial autocorrelation and spatial non-stationarity? If yes could you explain the differences and novel methods to address them?
Hi, I am using the randomForest package for species distribution modelling. I am facing two problem in this work. First when fitting the model i am getting warning message: "Warning message:
In randomForest.default(m, y, ...) :
The response has five or fewer unique values. Are you sure you want to do regression?"
I am also getting error mesg when predicting the model in raster stack of env. variables as :
"n eval(predvars, data, env) : object 'X' not found"
Could you explain me the reason for such warning/error message?
I will be grateful if you have any tutorials to use randomforest in species distribution modelling.
Thank you
