Spectral quality assessment of Landsat 8 and Sentinel 2 bands for glacier identification in Upper Indus Basin

• Main Authors: Hassan, Syed Najam Ul, Md. Reba, Mohd. Nadzri, Hussain, Dostdar, Ahmed, Aftab
• Format: Conference or Workshop Item
• Published: 2018
• Subjects: G109.5 Global Positioning System
• Online Access: http://eprints.utm.my/id/eprint/83914/; https://www.researchgate.net/publication/328800905_Spectral_quality_assessment_of_Landsat_8_and_Sentinel_2_bands_for_glacier_identification_in_Upper_Indus_Basin

Glacier studies of Hindu Kush Karakoram Himalaya (HKKH) are inadequate where, the stability of glaciers in the Upper Indus Basin (UIB) of HKKH is known for anomaly studies. Despite of satellite based synoptic measuring schema, the quality of glacier anomaly estimate is always on debate. The advancement in Operational Land Imager (OLI) and Multi Spectral Instrument (MSI) offers the potential future of glacier measurement in UIB. Therefore, this study assesses the quality of OLI and MSI in mapping the glacier anomaly for glaciers of Hunzza in UIB. The methodology is based on acquisition of Landsat Enhanced Thematic Mapper Plus (ETM+) Level 1C and OLI Level 2 data, while for Sentinel MSI Level 2A data was derived using Level 1C. Both OLI and MSI were calibrated with uncertainty of 3% than 5% of the raw ETM+. Glacier outlines extracted from the Randolph Glacier Inventory and the snow line altitude (SLA) demarcated through contour generation from Global Digital Elevation Model (GDEM) to differentiate permanent snow and clear ice in the overall glacier polygon. Reflectance of each band was derived and Normalized Snow Differential Index (NDSI) calculated. Statistics applied in spectral quality assessment for glacier parameters. Overall glacier surface exhibited range of reflectance about 0.08 to 0.12, 0.07 to 0.11 and 0.06 to 0.09 at visible bands of OLI that was differed about 20%, 22% and 25% than that of MSI. Where, in infrared band both sensors agreed by the reflectance of 0.10. Reflectance correlation between both sensors derived as 0.7 to 0.9 at visible band and 0.5 to 0.6 at infrared which, allows clear discrimination between the clear ice and snow. But the overlap of reflectance within 0.2 to 0.5 and 0.35 and 1.0 in MSI bands led to erroneous identification. To complement the results, NDSI of OLI with 0 to 0.25 and 0.75 to 1.0 becomes good indicator to distinguish different glacier features with disadvantage of inconsistent in MSI. These results clearly show that OLI and MSI have promising capability to map glacier anomaly and both variants can be synergized for better interpretation in climacterically intrinsic high-altitude zone of UIB.