Snow Geophysical Parameters Retrieval Using Prisma Hyperspectral Data Over The South Lhonak Glacier Region

Snow geophysical properties, an important indicator of cryospheric hazards, are essential to understand when investigating the snow/glacier system. This study aims to estimate the geophysical properties, such as density, wetness, and size of the grains, around South Lhonak Glacier, Sikkim, India, after the Glacial Lake Outburst Flood (GLoF) occurrence on October 4, 2023. The geophysical characteristics of snowpack are evaluated using data from the Italian Space Agency’s PRISMA hyperspectral mission, which was acquired on October 8, 2023. Utilizing the abundance fraction map and the commonly used Normalized Difference Snow Index (NDSI) threshold of 0.4, the snow cover mask over the region is generated at the subpixel label. A fast-iterative pixel purity index is used to obtain the endmembers for each grain size: coarse, medium, fine, and frost. Using the JHU snow grain size spectral library, these endmembers are identified. Spectral Angle mapper is used to perform the snow grain size mapping. Coarser snow was discovered to be more prevalent in the study region in the month of ablation, which agrees with the Himalayan field conditions. In addition, modified NIR-NDSI feature space is used for wetness; and dielectric and density are estimated using the methods of Singh and Bharti (2023). The estimated range of the density values corroborates well with the reported average density of mountain glaciers (830-927 $\mathrm{kg} / \mathrm{m}^{3}$). The study reports the efficacy of $1.03 \mu \mathrm{~m}$ in estimating the snow wetness and grain size.

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Published
2024-12-02
DOI
https://doi.org/10.1109/ingarss61818.2024.10984165
Citations
1
Primary Topic
Cryospheric studies and observations
Type
article
Field-Weighted Citation Impact
0.38
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article

Snow Geophysical Parameters Retrieval Using Prisma Hyperspectral Data Over The South Lhonak Glacier Region

Manmit Kumar Singh, Rishikesh Bharti
1 citations
Cryospheric studies and observations
0.38
article

Snow Geophysical Parameters Retrieval Using Prisma Hyperspectral Data Over The South Lhonak Glacier Region

Manmit Kumar Singh, Rishikesh Bharti
article en
1 citations

Abstract

Snow geophysical properties, an important indicator of cryospheric hazards, are essential to understand when investigating the snow/glacier system. This study aims to estimate the geophysical properties, such as density, wetness, and size of the grains, around South Lhonak Glacier, Sikkim, India, after the Glacial Lake Outburst Flood (GLoF) occurrence on October 4, 2023. The geophysical characteristics of snowpack are evaluated using data from the Italian Space Agency’s PRISMA hyperspectral mission, which was acquired on October 8, 2023. Utilizing the abundance fraction map and the commonly used Normalized Difference Snow Index (NDSI) threshold of 0.4, the snow cover mask over the region is generated at the subpixel label. A fast-iterative pixel purity index is used to obtain the endmembers for each grain size: coarse, medium, fine, and frost. Using the JHU snow grain size spectral library, these endmembers are identified. Spectral Angle mapper is used to perform the snow grain size mapping. Coarser snow was discovered to be more prevalent in the study region in the month of ablation, which agrees with the Himalayan field conditions. In addition, modified NIR-NDSI feature space is used for wetness; and dielectric and density are estimated using the methods of Singh and Bharti (2023). The estimated range of the density values corroborates well with the reported average density of mountain glaciers (830-927 $\mathrm{kg} / \mathrm{m}^{3}$). The study reports the efficacy of $1.03 \mu \mathrm{~m}$ in estimating the snow wetness and grain size.

Indian Institute of Technology Guwahati (IN)
Climate action
Openalex Percentile: Top 36%
Cryospheric studies and observations
0.38
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Snow Geophysical Parameters Retrieval Using Prisma Hyperspectral Data Over The South Lhonak Glacier Region — Manmit Kumar Singh, Rishikesh Bharti · (2024) | TGRS Research Map | TGRS