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RISS 인기검색어
- 검색키워드
- 저자 : Gouri Sankar Bhunia (검색결과 5 건)
- 무료
- 기관 내 무료
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Soil organic carbon stock explored by geo-spatial modeling at Sagar Island, India
Gouri Sankar Bhunia,Pravat Kumar Shit,Ramkrishna Maiti 대한공간정보학회 2016 Spatial Information Research Vol.24 No.5
Soil organic carbon (SOC) and organic carbon density (OCD) is an active indicator of soil fertility and productivity, and it fluctuates spatially and temporally. The main objective of the present study is to evaluate the spa- tial variability of SOC and OCD using geostatistics model as well as field methods at Sagar Island (Sundarban), India. Soil samples at the depths of 0–20 cm were collected from twenty plots at different season to estimate organic carbon concentrations and carbon density in the laboratory. Spatial distributions of SOC and OCD concentrations were esti- mated using ordinary kriging method. Remote sensing imagery and ground truth helped in identifying different features as well as land use/land cover correctly. Landuse are characterized by coastal water, sand, coastal wetland, salt marsh, agricultural fallow land, sparse vegetation, crop/paddy field, and mixed settlement area. The average value SOC were recorded as 2.80, 1.83, and 2.069 % in post-monsoon, pre-monsoon and monsoon season respec- tively. Semivariograms models of SOC and OCD in all seasons illustrated strong positive nugget values indicated short scale variability and sampling error. The coefficient of determination (R2 ) of the SOC model denoted as 0.71, 0.68 and 0.74 and for OCD calculated as 0.78, 0.67 and 0.83 at pre-monsoon, monsoon and post-monsoon season respectively. The results illustrated that mangrove forest portrayed highest amount of SOC concentration in both the pre-monsoon (1.05 kg/m2 ) and post-monsoon (0.94 kg/m2 ) season.
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Spatial clustering of Plasmodium falciparum in Bihar (India) from 2007 to 2015
Gouri Sankar Bhunia,Niyamat Ali Siddiqui,Department of Biostatistics,Nandini Chatterjee,Sanjay Kumar Sinha 대한공간정보학회 2016 Spatial Information Research Vol.24 No.6
Malaria is the leading cause of morbidity and mortality in Bihar (India), and concomitant with the spatial and temporal discrepancy throughout the region. Present study aims to determine the changes in spatial distribution of Plasmodium falciparum in Bihar from year 2007–2015. We used Moran’s I indices and Getis-Ord Gi* statistics to determine the spatial clustering pattern of malaria. The highest variability of disease distribution was observed in 2009. The maximum spatial autocorrelation value was calculated in 2011 (Moran’s I = 0.62, p\0.00001). Results of cluster-outlier analysis showed significant high– high clustered. Plasmodium falciparum were spread in the western part of the state from 2007 to 2015. Most of the hotspot districts were observed in the south-west corner of the state. Furthermore, temporal disparities in malaria incidence were also observed. There is an intense change in the spatial clustering pattern of P. falciparum malaria within a 9-year period. Malaria hot spots are exhibited as risk maps that are valuable for observing and spatial targeting of deterrence and control actions against the disease.
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Channel dynamics associated with land use/cover change in Ganges river, India, 1989–2010
Gouri Sankar Bhunia,Pravat Kumar Shit,Dilip Kumar Pal 대한공간정보학회 2016 Spatial Information Research Vol.24 No.4
Shifting river courses and braiding in large rivers are part and parcel in fluvial morphology. The study aims at probing the changes of the Ganges river courses with accompanying land use/land cover characteristics. Here the changes that took place over a period ranging a couple of decades were recorded using multi-temporal Landsat 4–5 Thematic Mapper data. Meander geometry was precisely estimated. River course change pattern along with the changes in land use/land cover were studied over the period of 21 years (1989–2010). Results showed 0.14 km bank erosion and 0.85 km valley area was prone to erosion during the entire study period. The study exhibited the active channel area decreased by 22.88 km2 (0.33 % of the original river course) from 1989 to 2010. Land use characteristics showed settlement and plantation with settlement and crop lands were increased, whereas agricultural land was decreased in the study area. The overall kappa statistics were recorded as more than 0.84 during the study period. Rivers tend to maintain its high volume flow by eschewing additional silt load through bank overflow, called flash flooding; which is a natural process for any river to maintain the health of its thalweg.
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Spatio-temporal analysis of COVID-19 in India – a geostatistical approach
Bhunia Gouri Sankar,Roy Santanu,Shit Pravat Kumar 대한공간정보학회 2021 Spatial Information Research Vol.29 No.5
Coronavirus (Covid) is a severe acute respiratory syndrome infectious disease, spreads primarily between human beings during close contact, most often through the coughing, sneezing, and speaking small droplets. A retrospective surveillance research is conducted in India during 30th January–21st March 2020 to gain insight into Covid’s epidemiology and spatial distribution. Voronoi statistics is used to draw attention of the affected states from a series of polygons. Spatial patterns of disease clustering are analyzed using global spatial autocorrelation techniques. Local spatial autocorrelation has also been observed using statistical methods from Getis-Ord Gi *. The findings showed that disease clusters existed in the area of research. Most of the clusters are concentrated in the central and western states of India, while the north-eastern countries are still predominantly low-rate of clusters. This simulation technique helps public health professionals to identify risk areas for disease and take decisions in real time to control this viral disease.
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Anukul Ch Mandal,Poly Patra,Raja Majumder,Debashish Kumar Ghosh,Gouri Sankar Bhunia 대한공간정보학회 2018 Spatial Information Research Vol.26 No.1
Discernibility of Bhagirathi river course change detection was prepared via Remote Sensing and GIS in Murshidabad district among 41 years of period (1977–2017). Landsat MSS, TM, ETM?, TM, OLI sensor data from 1977, 1990, 2000, 2010 and 2017 respectively were considered to demarcate the chronological changes of the river course. Normalized Difference Water Index was used to extract the surface water bodies. Seventy-seven cross sections have been drawn to delimit the river course shifting pattern. The results shows that he Bhagirathi river course has been shifting towards south and west direction in different places, particularly in the lower and middle courses of the river. The adjacent riverine region has remained undeveloped due to infrastructure damaged by flood, changing course. Therefore, present study may be helpful for the overall management and planning for future prevention of flood, changing course, loss of properties.
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