Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Monitoring Gangotri Glacier Using Remote Sensing and GIS Technique

Author : Surender Kumar 1

Date of Publication :10th January 2018

Abstract: The Gangotri Glacier is the most important natural phenomena of the Indian civilization during the ancient period. It monitoring in the regular interval is difficult. The health of this Glacier involved a crucial role for the local and Himalayan ecosystem and climatic condition. So here a small approach to monitoring the Glacier 2001 and 2017 Landsat data used for the investigation. All type of correction (geometric, radiometric and atmospheric) have been done for to get actual reflectance value, then normalized snow index(NDSI) and normalized vegetation index(NDVI) have been calculated the present condition of the Gangotri Glacier status have been analyzed using base on NDVI and NDSI. The NDVI and NDSI are most prominent and popular band statistics method to observing snow cover and vegetation cover mapping. The maximum observed ndvi Values close to zero -0.1 to 0.1, it mean area rocks or snow and values approaching -1 mean water which indicate glacial small water body. After the comparison of the data set between 2001 and 2017 by NDVI and NSDI the Gangotri glacier is rerating during previous period the data clearly show that the differentiation of snow and vegetation porn areas.

Reference :

    1. Kouh, M.N., I. M. Bahuguna., Ajai., A. S. Rajawat., Sadiq. Ali., Sumit. Koul. 2016. “Glacier Area Change over Past 50 Years to Stable Phase in Drass Valley, Ladakh Himalaya (India).” American Journal of Climate Change. 5: 88-102.
    2. Srivastava, D. 2012. Status Report on Gangotri Glacier, Science and Engineering Research Board,Department of Science and Technology, New Delhi, Himalayan. Glaciology Technical ReportNo. 3, 102.
    3. Ghosh, P.,2017. “Remote Sensing and GIS Analysis of Gaumukh Snout Retreat and Ice Loss Estimation at Gangotri Glacier, During 1962-2015”. Global Journal of Current Research 5 (3): 113-119.
    4. Bhambri,R.,Tobis. Bolch.,Ravinder. Kumar. Chaujar., Subhas. Chandra.Kulshreshtha., “Glacier changes in the Garhwal Himalaya, India, from 1968 to 2006 based on remote sensing”. Journal of Glaciology, 57(203): 543- 556.
    5. Winsvold,S.H.,Andreas.Kaab.,Christopher.Nuth.“Regi onal Glacier Mapping Using Optical Satellite Data Time Series”. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING.:1-13.
    6. Aggarwal,S.P.,Praveen.K.,Thakur.BhaskarR.,Nikam.V aibhav. Garg., 2014.“Integrated approach for snowmelt run-off estimation using temperature index model,remote sensing and GIS”. Current Science 106 (3):397-407.
    7. Kouh, M.N., I. M. Bahuguna., Ajai., A. S. Rajawat., Sadiq. Ali., Sumit. Koul. 2016. “Glacier Area Change over Past 50 Years to Stable Phase in Drass Valley, Ladakh Himalaya (India).” American Journal of Climate Change. 5: 88-102
    8. Kundu,S.,2015. “Delineation of glacial zones of Gangotri and other glaciers of Central Himalaya using RISAT-1 C-band dual-pol SAR”. International Journal of Remote Sensing.36:6. 1529-1550, DOI: 10.1080/01431161.2015.1014972.
    9. Haq,M.Anul.,Kamal.Jain.,K.P.R.Menon.2011.“CHAN GE MONITORING OF GANGOTRI GLACIER USING SATELLITE IMAGERY”. Esri India User Conference :12Th.
    10. Satyabala,S.P.,2016. “Spatiotemporal variations in surface velocity of the Gangotri glacier, Garhwal Himalaya, India: Study using synthetic aperture radar data.” Remote Sensing of Environment (181):151-161.
    11. Wang, Xiao-Yan., Jian. Wang., Zhi. Yong. Jiang., Hong. Yi. Li., Xiao. Hua. Hao., 2015 .“An Effective Method for Snow-Cover Mapping of Dense Coniferous Forests in the Upper Heihe River Basin Using Landsat Operational Land Imager Data” Remote Sens 7: 17246– 17257. doi:10.3390/rs71215882

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