Multi-sensor remote sensing to map glacier debris cover in the Greater Caucasus, Georgia

Holobâcă, Iulian‐Horia; Tielidze, Levan; Ivan, Kinga; Elizbarashvili, Mariam; Alexe, Mircea; Germain, Daniel; Petrescu, Sorin Hadrian; Pop, Olimpiu; Gaprindashvili, George

doi:10.1017/jog.2021.47

Cited by 15 publications

(9 citation statements)

References 69 publications

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“…Paul and others (2015) have reported that errors involved in mapping glaciers can be significant when glaciers are heavily debris-covered and that this is a major challenge for glaciological studies (Shukla and others, 2010; Paul and others, 2015). The complex physical characteristics of debris-covered ice make it difficult to map with optical remote sensing (Holobâcă and others, 2021). Most studies are limited to small geographical regions and where only a small number of glaciers (<5) are analyzed (Robson and others, 2015; Kaushik and others, 2019).…”

Section: Discussionmentioning

confidence: 99%

Patterns and drivers of glacier debris-cover development in the Afghanistan Hindu Kush Himalaya

Shokory

Lane

2023

J. Glaciol.

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Debris-covered ice is widespread in mountain regions with debris an important control on surface ice melt and glacier retreat. Quantifying debris cover extent and its evolution through time over large regions remains a challenge. This study develops two Normalized Difference Supraglacial Debris Indices for mapping debris-covered ice based on thermal and near Infrared Landsat 8 bands. They were calibrated with field data. Validation suggests that they have a high level of accuracy. They are then applied to Landsat data for 2016 to produce the first detailed glacier inventory of the Afghanistan Hindu Kush Himalaya that includes debris cover. 3408 glaciers were identified which, for those ⩾0.01 km2 in area, gives an ice cover of 2,222 ± 11 km2 and a debris cover of 619 ± 40 km2. Principal components analysis was used to identify the most influential drivers of debris-covered ice extent. Lower proportions of debris cover were associated with glaciers with a higher elevation range, that were larger, longer and wider. These relations were statistically clearer when the dataset was broken down into climate and geological zones. A glaciers continue to shrink, the proportion of debris cover will become higher, making it more important to map debris cover reliably.

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Section: Discussionmentioning

confidence: 99%

Patterns and drivers of glacier debris-cover development in the Afghanistan Hindu Kush Himalaya

Shokory

Lane

2023

J. Glaciol.

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“…Given that manual glacier delineation is problematic for debris cover and/or snowfields [42], many fully automatic methods have emerged [43]. Additionally, the comprehensive multi-platform datasets of SAR coherence images were also combined and applied with visible, thermal spectrums and DEM [44].…”

Section: Glacier Delineationsmentioning

confidence: 99%

Remote Sensing and Modeling of the Cryosphere in High Mountain Asia: A Multidisciplinary Review

Ye,

Wang,

Liu

et al. 2024

Remote Sensing

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Over the past decades, the cryosphere has changed significantly in High Mountain Asia (HMA), leading to multiple natural hazards such as rock–ice avalanches, glacier collapse, debris flows, landslides, and glacial lake outburst floods (GLOFs). Monitoring cryosphere change and evaluating its hydrological effects are essential for studying climate change, the hydrological cycle, water resource management, and natural disaster mitigation and prevention. However, knowledge gaps, data uncertainties, and other substantial challenges limit comprehensive research in climate–cryosphere–hydrology–hazard systems. To address this, we provide an up-to-date, comprehensive, multidisciplinary review of remote sensing techniques in cryosphere studies, demonstrating primary methodologies for delineating glaciers and measuring geodetic glacier mass balance change, glacier thickness, glacier motion or ice velocity, snow extent and water equivalent, frozen ground or frozen soil, lake ice, and glacier-related hazards. The principal results and data achievements are summarized, including URL links for available products and related data platforms. We then describe the main challenges for cryosphere monitoring using satellite-based datasets. Among these challenges, the most significant limitations in accurate data inversion from remotely sensed data are attributed to the high uncertainties and inconsistent estimations due to rough terrain, the various techniques employed, data variability across the same regions (e.g., glacier mass balance change, snow depth retrieval, and the active layer thickness of frozen ground), and poor-quality optical images due to cloudy weather. The paucity of ground observations and validations with few long-term, continuous datasets also limits the utilization of satellite-based cryosphere studies and large-scale hydrological models. Lastly, we address potential breakthroughs in future studies, i.e., (1) outlining debris-covered glacier margins explicitly involving glacier areas in rough mountain shadows, (2) developing highly accurate snow depth retrieval methods by establishing a microwave emission model of snowpack in mountainous regions, (3) advancing techniques for subsurface complex freeze–thaw process observations from space, (4) filling knowledge gaps on scattering mechanisms varying with surface features (e.g., lake ice thickness and varying snow features on lake ice), and (5) improving and cross-verifying the data retrieval accuracy by combining different remote sensing techniques and physical models using machine learning methods and assimilation of multiple high-temporal-resolution datasets from multiple platforms. This comprehensive, multidisciplinary review highlights cryospheric studies incorporating spaceborne observations and hydrological models from diversified techniques/methodologies (e.g., multi-spectral optical data with thermal bands, SAR, InSAR, passive microwave, and altimetry), providing a valuable reference for what scientists have achieved in cryosphere change research and its hydrological effects on the Third Pole.

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“…The delineation process is challenging for debris-covered glaciers. Various studies have focused on the automatic delineation of debris-covered glaciers (Bhardwaj et al, 2014;Holobâcă et al, 2021;Mölg et al, 2018). In the present study, all the glaciers with an area > 0.5 km 2 have been studied, which include both clean-ice and debris-covered glaciers.…”

Section: Glacier Delineationmentioning

confidence: 99%

A comprehensive multidecadal glacier inventory dataset for the Chandra-Bhaga Basin, Western Himalaya, India

Vatsal

Bhardwaj

Azam

et al. 2022

Preprint

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Abstract. Delineation of Glaciers is a challenging task in the Himalaya due to its complex topography, cloud cover, seasonal snow cover, hillshade, debris cover. Glacio-hydrological studies including mass balance, run-off, and dynamic modelling rely on the availability of consistent and reliable glacier inventory datasets. This article on data set presents a homogenous, multidecadal inventory of glaciers in the Chandra-Bhaga Basin (CB Basin), western Himalaya, for 1993, 2000, 2010, and 2019. Landsat Thematic Mapper (TM), Enhanced Thematic mapper (ETM+), and Operational Land Imager (OLI) imageries, with minimum snow and cloud cover have been used for enhanced accuracy and consistency. Uncertainty assessment for the generated glacier inventory was performed, following various approaches such as buffer method, standard error estimation, and manual digitisation error and the maximum uncertainty has been quantified. We have identified and manually mapped a total of 251 glaciers with an area > 0.5 km2, and in order to minimise the uncertainty, field surveys were carried out on 6 glaciers in the basin. Out of these 251 glaciers, 217 are clean ice and 35 were debris-covered glaciers. The estimated total glacier area was 996 ± 62 km2 in 1993 that decreased to 973 ± 70 km2 in 2019. Apart from quantifying temporal changes in glacier area, this inventory further allows the estimation of supraglacial debris cover and glacier volume. The supraglacial debris cover area has increased by 14.1 ± 2.54 km2 (15.2 %) during 1993–2019. Accuracy of the debris cover dataset estimated using ground surveys is 82 % with a kappa coefficient of 0.87. Moreover, a glacier ice volume dataset was also generated by incorporating the inventory into Glacier Bed Topography Version 2 (GlabTop2) model and shows a total of 112.5 ± 41 km3 of ice volume stored in the CB Basin glaciers. For accuracy assessment of the DEMs generated using ASTER Stereopairs images, DGPS surveys were carried out on (28 GCPs) and off (6 GCPs) the glaciers. Glacier volume uncertainty with respect to the generated DEMs and model bias is 5.3 km3 and 35.5 km3 respectively. Overestimation of glacier volume due to over deepening is estimated to be 1.2 km3. The impact of climate change on the Himalayan glaciers is a matter of serious concern and such holistic multitemporal inventory datasets can help quantify that impact with improved certainty.

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Multi-sensor remote sensing to map glacier debris cover in the Greater Caucasus, Georgia

Cited by 15 publications

References 69 publications

Patterns and drivers of glacier debris-cover development in the Afghanistan Hindu Kush Himalaya

Patterns and drivers of glacier debris-cover development in the Afghanistan Hindu Kush Himalaya

Remote Sensing and Modeling of the Cryosphere in High Mountain Asia: A Multidisciplinary Review

A comprehensive multidecadal glacier inventory dataset for the Chandra-Bhaga Basin, Western Himalaya, India

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