Papers by Satiprasad Sahoo
Arabian Journal of Geosciences
With the advancement of globalisation, urbanisation and environmental change, the outbreak of the... more With the advancement of globalisation, urbanisation and environmental change, the outbreak of the Coronavirus disease 2019 (COVID-19), as an infectious disease, has become a global threat. The entire world is continuously trying to adapt to the pandemic situation due to the sudden outbreak of COVID-19 and the lockdown phase, which has not been faced before. The fear of infection by such an unknown virus and the epidemic transformed the built-up environment and impacted various sectors of lives and livelihoods, which must be assessed in spatial perspectives. The objective of this research is to assess the multisectoral impact due to the COVID-19 pandemic. Thus, it is designed to inspect seven essential sectors, namely, the economy, employment, education, transport, travel and tourism, health and environment sector-wise impact assessment of the West Bengal state of India. Taking the required COVID-19 data from the government website of India (http:// www. covid 19ind ia. org; https:// www. mygov. in/ corona-data/ covid 19-state wise-status) and West Bengal (https:// covid india. org/ west-bengal), a methodology is proposed on an integrated framework for the multi-sectoral impact assessment. The study concentrates on West Bengal, as no study exists on the multi-sectoral impact assessment due to the COVID-19 pandemic during the 1st wave, especially using the geospatial platform. The economy, employment, education, transport, health, tourism and environment multi-sectors of West Bengal are selected in this research, as these sectors have built the economic, sociocultural and environmental pillars of the state. All these sectors have been seriously affected, and the nature of the impact is diverse and large. Before the vaccine comes into the hands of the common people of West Bengal and in a broad sense in India, the awareness should be increased at the grass-root level to fight against the pandemic situation and even after the post-COVID era. The application of geospatial technology used for the mapping and analysis of COVID-19 affects the related database to tease out the multidimensional study, which aims to plan future road maps, search for answers and learn to add further security to overcome the future virus attack.
Springer, 2017
Land surface temperature (LST), land use/land
cover (LU/LC) and vegetation parameters are a subst... more Land surface temperature (LST), land use/land
cover (LU/LC) and vegetation parameters are a substantial
factor in worldwide climate change studies framework.
This study of investigating urban heat islands based on
thermal remote sensing data. Thermal infrared remote
sensing proved its capability in monitoring temperature and
affecting microclimate in urban areas. In the present study
have relationships among the multiple vegetation indices,
land use/land cover and LST using remote sensing techniques
in the Saranda forest state of Jharkhand. Normalized
difference vegetation index (NDVI), Soil-adjusted vegetation
index (SAVI), Ratio vegetation index (RVI) and
Normalized difference built-up index (NDBI) are used in
this study. The study work has been done on the correlation
of the association among the different vegetation indices,
land use/land cover, and land surface temperature. The
result shows that the external temperature an impact on
surfaces of self-heating (hot spots) areas. The relationship
between LST and NDVI result shows the negative correlation.
The NDVI proposes that the green land can deteriorate
the effect on mining, urban heat island while we
apparent the positive relationship between LST and NDBI.
This study demonstrates that the growth of the active
mining, the industrial area significantly decreases the
vegetation areas, hence grow the surface temperature. This
study also shows that the external temperature has an
impact on surfaces of self-heating (hot spots) areas.
Finally, the accuracy of proposed multiple indexes is
evaluated by using DGPS field survey points over the study
area. This analysis demonstrates the potential applicability
of the methodology for climate modeling framework.
Environmental Earth Sciences
To evolve a proper management scenario for groundwater utilization, identification of groundwater... more To evolve a proper management scenario for groundwater utilization, identification of groundwater potential zones is an important step. In the present study, an attempt has been made to identify possible groundwater potential zones both in terms of quantity and quality. A methodology is proposed for identification of groundwater potential index (GWPI) and a new water quality index (WQI) based on analytic hierarchy process. The proposed methodology has been applied to the shallow alluvial aquifer of central Ganga basin, Kanpur (India). Land use/land cover, soil, geology, recharge rate, drainage density, rainfall, slope, elevation, normalized difference vegetation index, groundwater depth or depth to groundwater table are used for GWPI calculation. Moreover, WQI considers alkalinity (as CaCO 3 ), magnesium (Mg 2? ), total dissolved solids and fluoride (F -) as influencing attributes. Final integration of attributes yield GWPI and WQI map. The resulting GWPI map has been classified into three groundwater potential zones namely: good, moderate and poor covering 26.94, 43.76, and 29.30 %, area, respectively. The WQI map has been classified into five quality zones namely: above permissible limit, poor, moderate, good, very good covering 12. 39, 7.63, 15.17, 38.18, and 26.64 % area, respectively. Monitoring data from well locations along with GWPI and WQI map reveals the proper potential zones. This analysis demonstrates the potential applicability of the methodology for a general aquifer system.
International Journal of Current Research
Watershed models such as SWAT (Soil and Water Assessment Tool) simulate land and water resource m... more Watershed models such as SWAT (Soil and Water Assessment Tool) simulate land and water resource management alternatives. To simulate these impacts, long-term daily rainfall data are necessary. In the absence of measured rainfall data, watershed models use weather generators to simulate rainfall events. The objective of this study is to examine average annual water balance variation generators in terms of the hydrologic response of SWAT. Hydrological and meteorological data for 12 years (1997 -2008) has been used to run the model. Most of the input data for the model are extracted from various maps and satellite images using GIS technique. The models range from field to watershed scales for simulating hydrology, sediment, nutrients, bacteria, and pesticides at temporal scales varying from hourly to annually.
Abstract The city of Baghdad is located in the central Mesopotamian plain of the Twin Rivers. Acc... more Abstract The city of Baghdad is located in the central Mesopotamian plain of the Twin Rivers. According to the geological surveys, the whole area is covered by recent sediments of alluvial origin, deposited by successive floods of Tigris and Euphrates rivers, and by wind ...
The Sundarbans is a rich biodiversity with tidal mangrove forest in the world. It is a part of de... more The Sundarbans is a rich biodiversity with tidal mangrove forest in the world. It is a part of deltaic plain of fluvial marine deposits of Ganges-Brahmaputra basin. The main aim of this study is to identify the best Supervised Classification method using linear regression model. Thus main focus goes to three supervised classification methods; these are Minimum Distance, Maximum Likelihood and Parallelepiped. We use linear regression model with NDVI (Normalized Differenced Vegetation Index) value and different classification area. Here we found that Maximum Likelihood classification is more accurate comparison to others, depends upon regression coefficient and ground based observation.
Groundwater depletion is a common problem in most of the states (INDIA). The western part of Odis... more Groundwater depletion is a common problem in most of the states (INDIA). The western part of Odisha is facing drinking water crisis almost every year due to large scale deforestation, unplanned use of irrigation water, unscientific or poor water management strategy. Hirakud command area, situated in the western part of Odisha, comes under Mahanadi river basin. In the present work, an analysis has been performed to delineate and classify possible groundwater potential zones in the Hirakud command area using integrated remote sensing and GIS techniques. Groundwater recharge potential depends on geological and hydrological characteristics of land surface. The groundwater potential zone index (GWPZI) map is generated by using Analytic Hierarchy Process (AHP) along with different influencing features, e.g., land use land cover, soil type, geology. All the feature layers have been integrated through GIS analysis and the groundwater potential zones have been delineated. Three zones have be...
Natural Resources Research, 2014
Environmental Earth Sciences, 2014
A hydro-environmental assessment has been performed for Hirakud command area (India) in terms of ... more A hydro-environmental assessment has been performed for Hirakud command area (India) in terms of quantity and physicochemical quality analysis of groundwater. Quantity analysis has been performed in terms of water level variation and groundwater potential zone identification. Groundwater table fluctuation analysis reveals that water level is declining rapidly due to insufficient recharge owing to frequent recession of monsoon and excessive pumping of groundwater. Inefficient distribution of canal water especially in the tail end of the Hirakud command is accentuating the high dependency on ground water. The groundwater potential zone index map is generated using analytic hierarchy process along with different influencing features, e.g., land use/cover, soil type, geology. Three zones have been identified for Hirakud command area (poor: 21.15 %, moderate: 46.32 %, and good: 32.53 %). Physical and chemical parameters of groundwater, e.g., electrical conductivity, pH, total dissolved solids, total hardness, nitrate, iron, sodium, potassium, calcium, magnesium, chlorine, bicarbonate and fluoride are analyzed for the study area. Piper analysis is used to identify dominant hydrochemical facies. United States Salinity Laboratory and Wilcox Diagram are used to determine the irrigation water quality. Principal component analysis is utilized to find out key groundwater quality parameters. The chemical analysis shows that values of all parameters are within permissible limit. However, nitrate, iron and fluoride are found above permissible limit in some areas. The assessment reveals the state of the aquifer in terms of quantity and quality.
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Papers by Satiprasad Sahoo
cover (LU/LC) and vegetation parameters are a substantial
factor in worldwide climate change studies framework.
This study of investigating urban heat islands based on
thermal remote sensing data. Thermal infrared remote
sensing proved its capability in monitoring temperature and
affecting microclimate in urban areas. In the present study
have relationships among the multiple vegetation indices,
land use/land cover and LST using remote sensing techniques
in the Saranda forest state of Jharkhand. Normalized
difference vegetation index (NDVI), Soil-adjusted vegetation
index (SAVI), Ratio vegetation index (RVI) and
Normalized difference built-up index (NDBI) are used in
this study. The study work has been done on the correlation
of the association among the different vegetation indices,
land use/land cover, and land surface temperature. The
result shows that the external temperature an impact on
surfaces of self-heating (hot spots) areas. The relationship
between LST and NDVI result shows the negative correlation.
The NDVI proposes that the green land can deteriorate
the effect on mining, urban heat island while we
apparent the positive relationship between LST and NDBI.
This study demonstrates that the growth of the active
mining, the industrial area significantly decreases the
vegetation areas, hence grow the surface temperature. This
study also shows that the external temperature has an
impact on surfaces of self-heating (hot spots) areas.
Finally, the accuracy of proposed multiple indexes is
evaluated by using DGPS field survey points over the study
area. This analysis demonstrates the potential applicability
of the methodology for climate modeling framework.
cover (LU/LC) and vegetation parameters are a substantial
factor in worldwide climate change studies framework.
This study of investigating urban heat islands based on
thermal remote sensing data. Thermal infrared remote
sensing proved its capability in monitoring temperature and
affecting microclimate in urban areas. In the present study
have relationships among the multiple vegetation indices,
land use/land cover and LST using remote sensing techniques
in the Saranda forest state of Jharkhand. Normalized
difference vegetation index (NDVI), Soil-adjusted vegetation
index (SAVI), Ratio vegetation index (RVI) and
Normalized difference built-up index (NDBI) are used in
this study. The study work has been done on the correlation
of the association among the different vegetation indices,
land use/land cover, and land surface temperature. The
result shows that the external temperature an impact on
surfaces of self-heating (hot spots) areas. The relationship
between LST and NDVI result shows the negative correlation.
The NDVI proposes that the green land can deteriorate
the effect on mining, urban heat island while we
apparent the positive relationship between LST and NDBI.
This study demonstrates that the growth of the active
mining, the industrial area significantly decreases the
vegetation areas, hence grow the surface temperature. This
study also shows that the external temperature has an
impact on surfaces of self-heating (hot spots) areas.
Finally, the accuracy of proposed multiple indexes is
evaluated by using DGPS field survey points over the study
area. This analysis demonstrates the potential applicability
of the methodology for climate modeling framework.