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Relationship between the variations in glacier features classified on a large scale with climate variables: a case study of Gangotri Glacier

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Abstract

Changes in glacier area, glacial lakes, debris cover, and geomorphological features such as debris fans have a significant impact on glacial dynamics. Therefore, precise and timely observation and tracking of glacier surface changes is a necessity. The availability of high spatial resolution remote sensing images has made it viable to analyse the glacier surface changes at a local level. However, with an increase in spatial resolution, the spectral variability increases, giving rise to additional challenges (such as false changes and misregistration) in the change detection process. These challenges can preferably be dealt with using an object-based change detection (OBCD) approach rather than the conventional pixel-based change detection approach. Therefore, this study has proposed an OBCD methodology using high-spatial-resolution remote sensing images to detect changes in glacier features. Variability in glacier features has been further analysed by associating it with important climate variables, that is, air temperature and precipitation. As a case study, the changes in Gangotri Glacier (Uttarakhand Himalayas in India) features have been studied using high-spatial-resolution WorldView-2 and Linear Imaging Self-Scanning System (LISS)-4 images for a 3-year period 2011–2014. The spectral correspondences between glacier surface and non-glacier surface have been handled by considering brightness temperature and slope as ancillary data to improvise their distinction. A change detection accuracy of ~ 84% has been obtained using the OBCD approach. Results further show that the variations in glacier features are in congruence with the climatic observations.

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Data availability

ASTER GDEM is a product of Japan’s Ministry of Economy, Trade, and Industry (METI) and NASA and is available at https://doi.org/10.5067/ASTER/ASTGTM.002. Landsat TM and TIRS images courtesy of the US Geological Survey. Landsat 4–5 TM Digital Object Identifier (DOI) number: /https://doi.org/10.5066/F7N015TQ and Landsat 8 TIRS Digital Object Identifier (DOI) number: /https://doi.org/10.5066/F71835S6.

Code availability

Not applicable.

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Acknowledgements

This work is an extension of the author’s own published work from conferences: https://doi.org/https://doi.org/10.1109/IGARSS.2018.8519230 and https://doi.org/https://doi.org/10.5194/egusphere-egu23-252. Kavita Vaijanath Mitkari is thankful to Dr. Hemendra Gusain, a scientist at the Institute of Technology Management (Defence Research and Development Organisation), Mussoorie, Uttarakhand, India, for his valuable suggestions during the project execution. We are grateful to all the anonymous reviewers including the reviewers of the special issue ‘Recent advances in remote sensing for sustainable environment’ for their constructive comments which has improved the quality of this paper.

Funding

This research was funded by the Science and Engineering Research Board, Department of Science and Technology, Government of India (Grant number SB/DGH/59/2013).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Punjab Engineering College (Deemed to be University), Sector 12, Chandigarh, 160012, India

    Kavita Vaijanath Mitkari & Sanjeev Sofat

  2. Mangalagiri-Mandal, Neeru Konda, SRM University, Amaravati, Andhra Pradesh, 522502, India

    Manoj Kumar Arora

  3. Department of Civil Engineering, Indian Institute of Technology Ropar, Rupnagar, Punjab, 140001, India

    Reet Kamal Tiwari

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  1. Kavita Vaijanath Mitkari
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  2. Sanjeev Sofat
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  4. Reet Kamal Tiwari
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Contributions

KVM, SS, MKA, and RKT conceptualised the work. Methodology formulation, data processing, and analysis were performed by KVM. KVM and RKT further investigated the results, and MKA supported the analysis. The required resources were provided by SS and RKT. The original draft manuscript was written by KVM. The manuscript was reviewed and edited by SS, MKA, and RKT. The data processing and change analysis were conducted at Punjab Engineering College (Deemed to be University), Chandigarh, India. Experiments to link the changes in glacier features with climate variables, including writing and editing the manuscript, were performed at Geomatics Engineering Lab, Indian Institute of Technology Ropar, Rupnagar, Punjab, India.

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Correspondence to Kavita Vaijanath Mitkari.

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Mitkari, K.V., Sofat, S., Arora, M.K. et al. Relationship between the variations in glacier features classified on a large scale with climate variables: a case study of Gangotri Glacier. Environ Monit Assess 196, 254 (2024). https://doi.org/10.1007/s10661-024-12417-4

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