Integrating CARTOSAT-1 and ASTER Digital Elevation Models to Refine and Enhance Long-Term Geodetic Glacier Mass Balance: A Case Study of Chhota Shigri Glacier, Western Himalaya

Abstract ID: 3.10956 | Not reviewed | Requested as: Poster | TBA | TBA

Tarang Patadiya (1)
Saurabh, Vijay (1)

(1) Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, India, Indian Institute of Technology Roorkee, Roorkee, India, 247667.

Categories: Cryo- & Hydrosphere
Keywords: Glacier Mass Balance, Chhota Shigri Glacier, Western Himalaya, Cartosat, ASTER

Categories: Cryo- & Hydrosphere
Keywords: Glacier Mass Balance, Chhota Shigri Glacier, Western Himalaya, Cartosat, ASTER

Abstract

Glacier mass balance is a key parameter for assessing glacier health and understanding its response to climate change. Previous studies have utilized various satellite-based techniques, such as stereo imaging, InSAR, and altimetry, to estimate geodetic glacier mass balance. However, these methods are often limited by either temporal constraints or sensor resolution. In this study, we combined time-series elevation data from CARTOSAT-1 and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) to provide an up-to-date geodetic glacier mass balance estimate for the period of 2002-2024. While ASTER, operational since 2000, offers spatial (30 m) and radiometric (8 bit) resolutions, CARTOSAT-1, which operated from 2005 to 2018, had superior spatial (2.5 m) and radiometric (10 bit) resolutions. To improve the accuracy of ASTER-based elevation change (dh/dt) data, we corrected the ASTER trend using the CARTOSAT-1 data from 2006-2018. We then applied this correction function to update ASTER observations from 2002-2024. When compared with in-situ glaciological mass balance measurements, our approach showed improved accuracy for ASTER-based geodetic mass balance estimates. Our study emphasizes the value of combining dh/dt time-series from different datasets to enhance the accuracy of glacier mass balance estimates with high temporal resolution, applicable across entire regions.