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Featured researches published by Arpit Chouksey.


Land Surface and Cryosphere Remote Sensing III | 2016

Ice sheet features identification, glacier velocity estimation and glacier zones classification using high resolution optical and SAR data

Praveen K. Thakur; Ankur Dixit; Arpit Chouksey; S Aggarwal; A. Senthil Kumar

Ice sheet features, glacier velocity estimation and glacier zones or facies classification are important research activities highlighting the dynamics of ice sheets and glaciers in Polar Regions and in inland glaciers. The Cband inSAR data is of ERS 1/2 tandem pairs with one day interval for spring of 1996 and L-band PolinSAR data of ALOS-PALSAR-2 for spring of 2015 is used in glacier velocity estimation. Glacier classification is done using multi-temporal C-and L-band SAR data and also with single date full polarization and hybrid polarization data. In first part, a mean displacement of 9 cm day-1 was recorded using SAR interferometric technique using ERS 1/2 tandem data of 25-26 March 1996. Previous studies using optical data based methods has shown that Gangotri glacier moves with an average displacement of 4 cm and 6 cm day-1. As present results using ERS 1/2 data were obtained for one day interval, i.e., 25th March 05:00pm to 26th March 05:00 pm, 1996, variation in displacement may be due to presence of snow or wet snow melting over the glacier, since during this time snow melt season is in progress in Gangotri glacier area. Similarly the results of glacier velocity derived using ALOSPALSAR- 2 during 22 March – 19 April 2015 shows the mean velocity of 5.4 to 7.4 cm day-1 during 28 day time interval for full glacier and main trunk glacier respectively. This L-band data is already corrected for Faraday’s rotation effects by JAXA, and tropospheric correction are also being applied to refine the results. These results are significant as it is after gap of 20 years that DInSAR methods has given glacier velocity for fast moving Himalayan glacier. RISAT-1 FRS-1 hybrid data is used to create Raney’s decompositions parameters, which are further used for glacier zones classification using support vector machine based classification method. The Radarsat-2 and ALOS-PALSAR-2 fully polarized data of year 2010 and 2015 are also used for glacier classification. The identified and classified glaciers zones in Gangotri area are debris covered ice, clean ice, percolation zone, wet snow zone, ice wall, supra-glacier lakes and moraines, similarly ice sheet features and glacier landforms such as such as nunataks, wind scoop, glacier flow paths, moraine, horn, sastrugi, and crevasses were identified in Antarctic. RISAT-1 FRS-1 data was also successful in mapping the Crevasses hidden under wind-blown ice in Antarctic’s study area.


Archive | 2019

Hydrometeorological Hazards Mapping, Monitoring and Modelling

Praveen K. Thakur; S. P. Aggarwal; Pankaj R. Dhote; Bhaskar R. Nikam; Vaibhav Garg; C. M. Bhatt; Arpit Chouksey; Ashutosh Jha

Northwest Himalaya (NWH) has unique topographical and climate settings which makes this area prone to various types of hydrometeorological hazards such as flash floods, hail storms, glacier lake outburst floods, avalanches and mudflows. These hazards have high probability of turning into natural disasters if proper planning of natural resources, infrastructure and man-made structures is not done. Floods of June 2013 in Uttarakhand (Dobhal et al. 2013; Thakur et al. 2014) and 2014 floods of Srinagar (Bhatt et al. 2016) are prime examples of such hazards turning into the major disasters. Northwest Himalayan states in the last few years have experienced large number of hydrometeorological disasters such as high-intensity precipitation, cloud burst and subsequent flash flooding in downstream areas, snow avalanches, glacier lake outburst floods (GLOF), hail storms, drought and rainfall-induced mudflows (Kumar et al. 2015; Gupta et al. 2013; Kumar et al. 2012; Rana et al. 2012). This chapter gives an overview of various hydrometeorological hazards which are reoccurring in NWH and provides insights in few such hazards by providing some actual case studies related to such hazards.


Archive | 2019

Impact of Water Conservation Structures on Hydrology of a Watershed for Rural Development

Vinit Lambey; A. D. Prasad; Arpit Chouksey; Indrajeet Sahu

A watershed is an area of land from which all rain water drains to a common location. In their natural state, streams and their associated floodplains provide a variety of important functions including the movement of water and sediment, storage of flood waters, recharge of groundwater, treatment of pollutants, dynamic stability, and habitat diversity. Disturbances to this system, either natural or human-induced, places stress on the system and has the potential to alter structure and/or impair the ability of the stream to perform ecological functions. Water conservation structures are helpful in maintaining the desired flow requirement and sediment yield within the watershed area. In this study, Jonk River, a tributary of Mahanadi basin has been selected to assess the impact of conservation structures for disaster risk reduction, sustainable agriculture and rural development. The outlet of Jonk River is located near Rampur in Chhattisgarh. Total area of the watershed is computed as 3424 km2. Soil and Water Assessment Tool (SWAT) has been used to calculate the discharge and sediment flow on daily and monthly basis for the year of 2001 considering two case scenarios i.e. with and without ponds as conservation structure (20 ponds in the villages are considered along the buffer area of the centreline of jonk river). The simulated discharge and sediment flow data has been compared with the observed data and the correlation coefficient is found to be 0.84 & 0.77 respectively. The annual discharge and sediment flow value in “with pond scenario” has been detected to be reduced by 69.27 and 64.10% respectively. The results observed in the present work can be used for site suitability analysis of soil and water conservation structures in the areas those are prone to soil erosion and floods. The study also reveals that the applications of Geographic Information Systems (GIS) and Geospatial Data Management can be used efficiently for watershed management and rural development.


Environmental Earth Sciences | 2016

Retrieval of land surface temperature from Landsat 8 TIRS for the command area of Mula irrigation project

Bhaskar R. Nikam; Furkat Ibragimov; Arpit Chouksey; Vaibhav Garg; S. P. Aggarwal


Hydrology | 2017

Hydrological Modelling Using a Rainfall Simulator over an Experimental Hillslope Plot

Arpit Chouksey; Vinit Lambey; Bhaskar R. Nikam; Shiv Prasad Aggarwal; Subashisa Dutta


Proceedings of the National Academy of Sciences, India Section A: Physical Sciences | 2017

Hydrological Parameters Estimation Using Remote Sensing and GIS for Indian Region: A Review

Praveen K. Thakur; Bhaskar Ramchandra Nikam; Vaibhav Garg; Shiv Prasad Aggarwal; Arpit Chouksey; Pankaj R. Dhote; Surajit Ghosh


Current Science | 2017

Satellite-Based Mapping and Monitoring of Heavy Snowfall in North Western Himalaya and its Hydrologic Consequences

Bhaskar R. Nikam; Vaibhav Garg; Prasun Kumar Gupta; Praveen K. Thakur; A. Senthil Kumar; Arpit Chouksey; S. P. Aggarwal; Pankaj R. Dhote; Saurabh Purohit


Proceedings of the National Academy of Sciences, India Section A: Physical Sciences | 2017

Cryospheric Studies in Indian Himalayan and Polar Region: Current Status, Advances and Future Prospects of Remote Sensing

Praveen K. Thakur; Vaibhav Garg; Bhaskar Ramchandra Nikam; Arpit Chouksey; S Aggarwal; Pankaj R. Dhote


International Journal of Advanced Remote Sensing and GIS | 2017

Hydrological Simulation using Process Based and Empirical Models for Flood Peak Estimation

Arnab Saha; Praveen K. Thakur; Arpit Chouksey


Archive | 2016

Hydrological Modelling Using Rainfall Simulator over Experimental Hillslope Plot

Arpit Chouksey; Vinit Lambey; Bhaskar R. Nikam

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Praveen K. Thakur

Indian Institute of Remote Sensing

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Vaibhav Garg

Indian Institute of Remote Sensing

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Bhaskar R. Nikam

Indian Institute of Remote Sensing

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Pankaj R. Dhote

Indian Institute of Remote Sensing

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Bhaskar Ramchandra Nikam

Indian Institute of Remote Sensing

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A. Senthil Kumar

Indian Institute of Remote Sensing

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S Aggarwal

Indian Institute of Remote Sensing

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S. P. Aggarwal

Indian Institute of Remote Sensing

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Shiv Prasad Aggarwal

Indian Institute of Remote Sensing

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Vinit Lambey

Indian Institute of Remote Sensing

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