Glacier Area Changes Research Articles

Remote sensing monitoring of glacier area and volume changes in glacier-fed mountainous watershed on the Northern margin of the Qinghai-Tibet Plateau under climate change.

Steady glacier runoff is related to the security and resilience of water resources in meltwater recharge basins, so the status and change of glaciers and their response to climate change in the upper reaches have received widespread concerns. Here, the spatiotemporal characteristics of glacier wastage in the Upper Reaches of Shule River Basin (URSRB) driven by climate change were analyzed based on multi-source and multi-temporal remotely sensed images. Firstly, we extracted multi-temporal glacier outlines from the Landsat time series data using Google Earth Engine (GEE) for seven different periods every approximately 5years from 1990 to 2020. The spatiotemporal analysis of URSRB glaciers demonstrates a sustained reduction in glacier area from 481.07 ± 24.24 km2 in 1990 to 384.05 ± 22.71 km2 in 2020, corresponding to a glacier shrinkage rate of - 0.67 ± 0.23%/year, characterized by considerable temporal variability. Secondly, multi-temporal DEMs derived from ASTER stereo imagery spanning from 2000 to 2020 were used to compute the glacier surface elevation changes and determine the glacier mass loss. The overall glacier surface elevation change rate was - 0.32 ± 0.14m/year, equivalent to a mass balance of - 0.28 ± 0.12m w.e./year. Lastly, to better apprehend the long-term response of URSRB glaciers to climate change, studies on climate change were carried out based on the EAR5-Land reanalysis dataset. The long-term trend of glacier wastage is attributed to the increase in summer temperature, and the negative effects of increased summer temperature on glaciers exceeded the positive effects of increased annual precipitation. In summary, glaciers in the URSRB have experienced a significant area reduction and accelerated mass loss against the backdrop of climatic warming and humidification.

Monitoring of Glacier Area Changes in the Ili River Basin during 1992–2020 Based on Google Earth Engine

The Ili River Basin, a crucial transboundary river in the arid region of Central Asia, plays a significant role in the region’s ecology and water resources. However, current methods for monitoring glacier area changes in this region face challenges in automation and accuracy due to the complex terrain and climatic conditions. This study aims to evaluate the effectiveness of the Google Earth Engine (GEE) platform for monitoring glacier area changes in the Ili River Basin from 1992 to 2020, with a focus on improving data accuracy and processing efficiency. Utilizing the Landsat data series, we employed the random forest (RF) classification algorithm within the GEE platform to extract glacier areas, optimizing a multidimensional feature set using the Jeffries–Matusita (JM) distance method, and applied visual interpretation for data refinement. Our results demonstrated that the GEE platform, combined with the RF algorithm, provided high accuracy in glacier monitoring, achieving an overall accuracy of 89% and a kappa coefficient of 0.85. During the study period, the glacier area in the Ili River Basin decreased by 184.76 km2, with an average annual retreat rate of 6.84 km2, most notably between 3800 and 4400 m in elevation. The analysis revealed that temperature changes had a more pronounced impact on glacier dynamics than precipitation. This approach significantly enhances image utilization efficiency and data processing speed, offering a reliable tool for monitoring glacier dynamics. Future research should focus on integrating additional environmental variables and extending the temporal scope to further refine glacier dynamics modeling and predictions.

Observing glacier elevation changes from spaceborne optical and radar sensors – an inter-comparison experiment using ASTER and TanDEM-X data

Abstract. Observations of glacier mass changes are key to understanding the response of glaciers to climate change and related impacts, such as regional runoff, ecosystem changes, and global sea level rise. Spaceborne optical and radar sensors make it possible to quantify glacier elevation changes, and thus multi-annual mass changes, on a regional and global scale. However, estimates from a growing number of studies show a wide range of results with differences often beyond uncertainty bounds. Here, we present the outcome of a community-based inter-comparison experiment using spaceborne optical stereo (ASTER) and synthetic aperture radar interferometry (TanDEM-X) data to estimate elevation changes for defined glaciers and target periods that pose different assessment challenges. Using provided or self-processed digital elevation models (DEMs) for five test sites, 12 research groups provided a total of 97 spaceborne elevation-change datasets using various processing approaches. Validation with airborne data showed that using an ensemble estimate is promising to reduce random errors from different instruments and processing methods but still requires a more comprehensive investigation and correction of systematic errors. We found that scene selection, DEM processing, and co-registration have the biggest impact on the results. Other processing steps, such as treating spatial data voids, differences in survey periods, or radar penetration, can still be important for individual cases. Future research should focus on testing different implementations of individual processing steps (e.g. co-registration) and addressing issues related to temporal corrections, radar penetration, glacier area changes, and density conversion. Finally, there is a clear need for our community to develop best practices, use open, reproducible software, and assess overall uncertainty to enhance inter-comparison and empower physical process insights across glacier elevation-change studies.

Glacier area change and its impact on runoff in the Manas River Basin, Northwest China from 2000 to 2020

Glacier area change and its impact on runoff in the Manas River Basin, Northwest China from 2000 to 2020

Accelerating Glacier Area Loss Across the Andes Since the Little Ice Age

AbstractAndean glaciers are losing mass rapidly but a centennial‐scale context to those rates is lacking. Here we show the extent of >5,500 glaciers during the Little Ice Age chronozone (LIA; c. 1,400 to c. 1,850) and compute an overall area change of −25% from then to year 2000 at an average rate of −36.5 km2 yr−1 or −0.11% yr−1. Glaciers in the Tropical Andes (Peru, Bolivia) have depleted the most; median −56% of LIA area, and the fastest; median −0.16% yr−1. Up to 10 × acceleration in glacier area loss has occurred in Tropical mountain sub‐regions comparing LIA to 2,000 rates to post‐2000 rates. Regional climate controls inter‐regional variability, whereas local factors affect intra‐region glacier response time. Analyzing glacier area change by river basins and by protected areas leads us to suggest that conservation and environmental management strategies should be re‐visited as proglacial areas expand.

Glacier area change (1993–2019) and its relationship to debris cover, proglacial lakes, and morphological parameters in the Chandra-Bhaga Basin, Western Himalaya, India

Glacier area change (1993–2019) and its relationship to debris cover, proglacial lakes, and morphological parameters in the Chandra-Bhaga Basin, Western Himalaya, India

Spatiotemporal variations in glacier area and surface velocity of the northern Antarctic Peninsula during 2018–2022

Ice sheet serves as a crucial indicator for assessing climate change. Mass loss in recent remote sensing-based studies indicated that the Antarctic Peninsula has rapid rates of glacier retreat and speed up of surface velocity. However, observations of seasonal variability of ice speed are limited, and glacier-area changes require multi-temporal monitoring. This study investigated the changes in area and surface velocities of ∼375 glaciers on the northern Antarctic Peninsula (NAP) utilizing satellite images acquired by the Sentinel 1&2 satellites during 2018–2022. The results indicate that the glacier area reduced by approximately 166.1 ± 44.2 km2 (−0.2% ± 0.1% per year) during the study period, with an acceleration after 2020 (−0.4% ± 0.3% per year), and the most dramatic reduction happened on the eastern NAP. The maximum annual ice speeds on the NAP generally exceeded 3500 m per year, while the ice speeds in 2021 were the highest (exceeded 4210 m per year). The ice speed variability in austral autumn was higher than in other seasons, meanwhile the summer ice speeds showed an increasing trend. The glacier G012158E47018N, McNeile Glacier, glacier G299637E64094S and Drygalski Glacier showed the most remarkable ice speed variations represented by high daily velocities and strong fluctuations on their termini. Our results demonstrated that the variations in glacier area and seasonal ice speed on the NAP were responsive to the ice–ocean–atmosphere processes. Therefore, seasonal velocity and area variations should be considered when conducting accurate mass balance calculations, model validations and change mechanism analyses under climate warming scenarios.

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

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.

Hydrological response to climate change in a glacierized catchment in eastern Tien Shan, Central Asia

Study regionThe headwaters of Urumqi River basin located in eastern Tien Shan Study focusGlacier shrinkage in recent decades has caused the volume and timing of glacier-fed streamflow to change, which in turn has significantly impacted the water supply and ecological system in the vast arid land in Central Asia and drawn wide public attention. Based on a glacio-hydrologic degree-day model, the runoff mechanisms and processes of the glacier-fed catchment are revealed. New hydrological insights for the regionThe study found that about 51 % glacier coverage of the Urumqi Glacier No.1 catchment (UG1C) generates approximately 76 % glacier runoff, indicating that glacier melt comprises a significant water resource in the region. The different ways that the glacier melts in response to temperature versus precipitation on a daily scale by changing glacier mass balance can effectively stabilize streamflow, showing a strong capacity of the glacier to naturally adjust streamflow beneficially to water utilization by those downstream. Based on the sensitivity of modelled runoff to glacier change by comparing simulations using constant glacier cover that accommodated dynamic changes in glacier area, we found that the maximum volume of ice melt runoff during the past four decades appeared during the period 1996–2019, most likely around 2010.

Characterizing the Water Storage Variation of Kusai Lake by Constructing Time Series from Multisource Remote Sensing Data

In September 2011, Zhuonai Lake (ZL) in the northeast of Hoh Xil (HX) on the Qinghai–Tibet Plateau (QTP) broke out. The outburst event seriously changed the environmental hydraulics in this region. Due to the insufficient temporal resolution of observations, it is challenging to assess the impact of this event on short-period variations of water volumes in three lakes downstream of ZL. Combining multisource remote sensing data, we constructed long and high-temporal-resolution time series for the lake level, area, and lake water storage (LWS) of Kusai Lake (KL) to characterize the variabilities before and after the outburst. The water level, area, and LWS time series contain 1051 samples from 1990 to 2022, with uncertainties of 0.16 m, 2.5 km2, and 0.016 km3, respectively. The accuracies verified using the Database for Hydrological Time Series of Inland Waters (DAHITI) are 0.26 m, 2.64 km2, and 0.08 km3 for water level, area, and LWS, respectively. We characterized the LWS variations during the past 30 years based on the high temporal resolution LWS time series. Before the outburst, the 1-year and 3.5-year variations dominated the LWS time series, and there was no obvious semi-annual signal. After the outburst, the 3.5-year variation disappeared, and a strong semi-annual oscillation was observed. From 2012 to 2015, the periodic LWS variations in KL were disturbed by the ZL outburst and the subsequent outflow of KL led by the outburst. Regular cyclic signals have been restored since 2016, with an amplified annual fluctuation. By analysis, precipitation, evaporation, and glacier area change are excluded as driving factors of the pattern change in LWS variations of KL. It can be concluded that the altered recharge pattern of KL triggered by the outburst directly resulted in the observed changes in TWS behavior. For the first time, we identified the periodic patterns of LWS variations of KL during the past 30 years and revealed that the ZL outburst event significantly influenced these patterns. This finding contributes to the comprehensive understanding of the effects of the ZL outburst on downstream lake dynamics. Furthermore, the presented procedure for constructing long and high-resolution time series of LWS allows for monitoring and characterizing the short-period variabilities of Tibetan lakes that lack hydrological data.

How to handle glacier area change in geodetic mass balance

Abstract Innovations in geodesy enable widespread analysis of glacier surface elevation change and geodetic mass balance. However, coincident glacier area data are less widely available, causing inconsistent handling of glacier area change. Here we quantify the bias introduced into meters water equivalent (m w.e.) specific geodetic mass balance results when using a fixed, maximum glacier area, and illustrate the bias for five North American glaciers. Sites span latitudes from the northern U.S. Rocky Mountains (48°N) to the Central Alaska Range (63°N) between 1948 and 2021. Results show that fixed (maximum) area treatment subdues the m w.e. mass change signal, underestimating mass balance by up to 19% in our test cases. This bias scales with relative glacier area change and the mass balance magnitude. Thus, the bias for specific geodetic mass balances will be most pronounced across rapidly deglaciating regions. Our analysis underscores the need for temporally resolved glacier area in geodetic mass balance studies.

Divergent glacier area and elevation changes across the Tibetan Plateau in the early 21st century

With accelerated warming, mountain glaciers in most parts of the world have been in a state of continuous retreat in recent decades. Assessing glacier change and analyzing its influencing factors are essential for developing climate change mitigation and adaptation measures for a given region. This study provides a spatially explicit assessment and quantification of glacier changes in the early 21st century on the Tibetan Plateau (TP) at individual glacier and basin scales. We established a one-to-one correspondence between the Second Chinese Glacier Inventory (CGI-2, collected from 2004 to 2011) and a dataset of glacier inventory in Western China during 2017–2018 (CGI-2018). The majority of TP’s glaciers decreased in size with a mean area retreat rate during the investigated period of 4.1%/decade. In addition, a mean change of the median elevation of the glaciers of 6.7 m/decade was detected. Approximately 2.5% of the total number of glaciers mapped in CGI-2 disappeared, while 681 of them divided to 1758 glaciers as they retreated. The observed variations follow local trends and have different regional characteristics. Generally, the glaciers with the lowest retreat rates are found in the Karakorum and Kunlun Mountains, while those with high retreat rates are concentrated along the Gangdis and Tangula ranges. The observed changes in glaciers are mainly attributed to a significant increase in temperature. Other factors including glacier size, debris cover, orientation and mean elevation also contribute to the heterogeneity of glacier variability. This study provides for the first time a detailed spatially explicit analysis of the glacial changes on the TP in the early 21st century, substantially improving the understanding of glacier response patterns and supporting more sustainable utilization of regional water resources in the TP in the context of climate warming in the 21st century.

Automatic Extraction of the Calving Front of Pine Island Glacier Based on Neural Network

Calving front location plays a crucial role in studying ice–ocean interaction, mapping glacier area change, and constraining ice dynamic models. However, relying solely on visual interpretation to extract annual changes in the calving front of ice shelves is a time-consuming process. In this study, a comparative analysis was conducted on the segmentation obtained from fully convolutional networks (FCN), U-Net, and U2-Net models, revealing that U2-Net exhibited the most effective classification. Notably, U2-Net outperformed the other two models by more than 30 percent in terms of the F1 parameter. Therefore, this paper introduces an automated approach that utilizes the U2-Net model to extract the calving front of ice shelves based on a Landsat image, achieving an extraction accuracy of 58 m. To assess the model’s performance on additional ice shelves in the polar region, the calving front of the Totten and Filchner ice shelves were also extracted for the past decade. The findings demonstrated that the ice velocity of the Filchner ice shelf exceeded that of the Totten ice shelf. Between February 2014 and March 2015, the majority of the calving fronts along the Filchner Ice Shelf showed an advancing trend, with the fastest-moving front measuring 3532 ± 58 m/yr.

Unlocking archival maps of the Hornsund fjord area for monitoring glaciers of the Sørkapp Land peninsula, Svalbard

Abstract. Archival maps are an important source of information on the state of glaciers in polar zones and are very often basic research data for analysing changes in glacier mass, extent, and geometry. However, basing a quantitative analysis on archival maps requires that they be standardised and precisely matched against modern-day cartographic materials. This can be achieved effectively using techniques and tools from the field of geographic information systems (i.e. GIS). The objective of this research was to accurately register archival topographic maps of the area surrounding the Hornsund fjord (southern Spitsbergen) published by the Polish Academy of Sciences and to evaluate their potential for use in studying changes in the geometry of glaciers in the north-western part of the Sørkapp Land peninsula in the following periods: 1961–1990, 1990–2010, and 1961–2010. The area occupied by the investigated glaciers in the north-western Sørkapp Land decreased in the years 1961–2010 by 45.6 km2, i.e. by slightly over 16 %. The rate of glacier area change varied over time and amounted to 0.85 km2 yr−1 in the period 1961–1990 and sped up to 1.05 km2 yr−1 after 1990. This process was accompanied by glacier surface lowering by about 90–100 m for the largest land-terminating glaciers on the peninsula and by up to more than 120 m for tidewater glaciers (above the line marking their 1984 extents). The dataset is now available from the Zenodo web portal: https://doi.org/10.5281/zenodo.4573129 (Dudek and Pętlicki, 2021).

Glacier area changes in the Arctic and high latitudes using satellite remote sensing

ABSTRACT Glaciers have been retreating over the last century as a result of climate change, particularly in the Arctic, causing sea levels to rise, affecting coastal communities and potentially changing global weather and climate patterns. In this study, we mapped 2203 glaciers in Novaya Zemlya (Russian Arctic), Penny Ice Cap (Baffin Island), Disko Island (Qeqertarsuaq, Greenland) and part of Kenai (Alaska), using Object-Based Image Analysis (OBIA) applied to multispectral Landsat satellite imagery in Google Earth Engine (GEE) to quantify the glacier area changes over three decades. Between 1985–89 and 2019–21, the results show that the overall glacier area loss in Novaya Zemlya is 1319 ± 419 km2 (5.7% of area), 452 ± 227 km2 (6.6%) for Penny Ice Cap, 457 ± 168 km2 (23.6%) in Disko Island and 196 ± 84 km2 (25.7%) in Kenai. A total of seventy-three glaciers have disappeared completely, including sixty-nine on Disko Island, three in Novaya Zemlya and one in Kenai.

Glacier Change and Its Influencing Factors in the Northern Part of the Kunlun Mountains

The glaciers in northwest China are mainly distributed in the northern part of the Himalayas, the Kunlun Mountains, and the Tianshan Mountains. Glaciers are an important freshwater resource in the northern part of the Kunlun Mountains, and the melting of glaciers and snow provides an assured source of water for rivers on the southern edge of the Tarim Basin. Based on the first glacier inventory dataset on China (1968), the second glacier inventory dataset on China (2009), and the glacier inventory dataset on Western China in 2018, this study used DEM data, Landsat remote sensing images, and ERA5 atmospheric reanalysis data to investigate glacier change and its influencing factors with respect to the northern part of the Kunlun Mountains. The results showed that there were 9273 glaciers in the northern part of the Kunlun Mountains in 2018, with an area of about 11,762.72 km2, an ice inventory of about 1168.53 km3, and an average length per glacier of about 1.68 km. The glaciers were mainly distributed at altitudes of 5300–6100 m (7574.66 km2). From 1968 to 2018, the number of glaciers in the northern stretch of the Kunlun Mountains increased by 343, while the glacier area decreased by 2452.80 km2 (−0.14%/a). From 2009 to 2018, the glacier area at the altitude of 4900 m to 6100 m decreased in the northern section of the Kunlun Mountains, and the glacier area at the remaining altitude increased slightly (10.67 km2). From 1968 to 2018, the glacier area and glacier length in all river basins decreased. The relative rate of glacier area change in the Qarqan River basin from 2009 to 2018 was five times that of 1968–2009, and this needs significant attention. From 1968 to 2018, both temperature and precipitation increased to varying degrees, and the increase in precipitation was beneficial to the accumulation of glaciers. Therefore, the increase in temperature was the main cause of glacier change in the northern section of the Kunlun Mountains.

A comparative analysis of glacier and glacier-melt runoff changes in western and eastern Himalayan river basins

This study assesses the impact of glacier changes and their effects on glacier melt runoff over three different Himalayan river basins located in western Himalaya (i.e. Baspa and Ganga) and eastern Himalaya (Teesta). For computation of glacier melt runoff, a fully distributed snow-glacier melt runoff model viz. SPHY has been used. The glacier area changes have been computed by preparing the glacier maps for different years for all selected river basins viz. Baspa (for year 2000 & 2018), Ganga (for year 1990, 2000, 2010 and 2020) and Teesta (for year 2000 and 2020). Results showed that the glacier areas have noticeably reduced for all Himalayan river basins viz. Baspa (∼19.8%), Ganga (∼5.01%) and Teesta (∼5%). It has been observed that smaller glaciers have more significantly reduced than large glaciers. The strength of the glacier melt induced runoff computation has been evaluated with reference to observed discharge at different gauges in all selected river basins, which showed a reliable agreement between modeled and observed runoff (R2 > 0.7). To see the behavior of runoff for different glacier sized watersheds, the three basins have been divided into a number of watersheds. In Baspa four watersheds while for Ganga and Teesta basins, six watersheds have finally selected depending on quantum of glacier. As per the decadal computation of glacier melt scenarios for all river basins viz. Baspa (i.e. 2003–2010 and 2011–2018), Ganga (1986–1995, 1996–2005, 2006–2015, and 2011–2020) and Teesta (1996–2010 and 2006–2020), observations showed that watersheds having large glaciers, the melt runoff has increased, while in cases of the watersheds having small glaciers, the melt runoff has decreased due to reduced glacier cover. In case of Baspa basin, glacier melt runoff has decreased by 5% while for Ganga and Teesta basins it has increased by 1%. Similarly, for Baspa basin, snowmelt runoff has increased by 6% and for Ganga and Teesta it has decreased by 3%.

Future state of Norwegian glaciers: Estimating glacier mass balance and equilibrium line responses to projected 21st century climate change

Glaciers and ice caps in Norway are presently undergoing mass loss, areal reduction, and frontal retreat, mainly a result of increased summer ablation due to rising summer temperatures over Scandinavia, especially after 2000 CE. In this paper, the glacier mass-balance response of 10 Norwegian glaciers with continuous mass balance observations (>10 years) to climate projections from 1971–2000 to 2071–2100 have been estimated. Projected changes in mean summer temperature and mean winter precipitation from 1971–2000 to 2071–2100, applying the RCP8.5 emission scenario for five different regions in Norway; ‘Sogn og Fjordane’ and ‘Hordaland’, now Vestland County in western Norway, ‘Oppland’, now part of Innlandet County in eastern Norway, and Nordland County and Finnmark County, both in Northern Norway), range between +3.5°C and +5.0°C, and between +5% and +25%, respectively. These climate projections have been converted (by linear regression with overlapping observational mass-balance data) into specific surface glacier mass balance [winter balance ( Bw), summer balance ( Bs), and annual balance ( Ba) for 10 glaciers in Norway with mass-balance series [Ålfotbreen, Nigardsbreen (part of Jostedalsbreen), Austdalsbreen (part of Jostedalsbreen), Rembesdalskåka (part of Hardangerjøkulen), Blomstølskardsbreen (part of Søre Folgefonna), Storbrean, Hellstugubrean, Gråsubrean, Engabreen (part of Vestre Svartisen, Langfjordjøkelen (data: http://glacier.nve.no/glacier/viewer/ci/no/ ) yielding a total, cumulative surface glacier mass loss from 2000 to 2100 CE in the range of -85.2 ± 4 to -197.3 ± 10 m water equivalents. The estimated changes in equilibrium-line altitudes (ELAs), in the range of 230 ± 10 to 630 ± 30 m, indicate that the mean ELA may reach the upper part of 7 of the 10 glaciers included in this study [Ålfotbreen, Austdalsbreen, Rembesdalskåka, Blomstølskardsbreen, Gråsubrean, Engabreen and Langfjordjøkelen] by the end of the 21st century. The projected glacier mass loss and ELA rise, and thus changes in glacier length, area and volume, will most likely have profound consequences for future glacier hydrology (runoff), hydropower production, wildlife, ecosystems, glacier hazards, and tourism.

Using a Web Map Service to map Little Ice Age glacier extents at regional scales

Abstract Extending the record of glacier area changes into the past improves our understanding of climate change impacts. Although analogue maps showing historic glacier extents are abundant, digital outlines from before the satellite era are sparse as the digitisation of moraines and trimlines on freely available satellite images is challenging. With the now available very high-resolution images provided by Web Map Services (WMS), new doors are open for the precise digitisation. Here, we used the ESRI WMS to digitise Little Ice Age (LIA) glacier extents and present area changes since the LIA in four selected regions along with a detailed uncertainty analysis. We used modern glacier outlines as a starting point and additionally consulted Sentinel-2 images, the ArcticDEM and historic maps for interpretation. Dating records from the literature allowed calculating area change rates. In total, 493 LIA glaciers (4640 km2, now 891 ice bodies with 3590 km2) were digitised, yielding relative area changes of −20% (−0.14% a−1), −15% (−0.10% a−1), −26% (−0.16% a−1) and −61% (−0.19% a−1) for Alaska, Baffin Island, Novaya Zemlya and the tropics, respectively. The ESRI WMS images are a great asset to precisely map moraines and trimlines, but information about the timing of the related extents requires further sources.

Glacier area changes in Novaya Zemlya from 1986–89 to 2019–21 using object-based image analysis in Google Earth Engine

AbstractClimate change has had a significant impact on glacier recession, particularly in the Arctic, where glacier meltwater is an important contributor to global sea-level rise. Therefore, it is important to accurately quantify glacier recession within this sensitive region, using multiple observations of glacier extent. In this study, we mapped 480 glaciers in Novaya Zemlya, Russian Arctic, using object-based image analysis applied to multispectral Landsat satellite imagery in Google Earth Engine and quantify the area changes between 1986–89 and 2019–21. The results show that in 1986–89, the total glacierized area was 22 990 ± 301 km2, in 2000–01 the area was 22 525 ± 308 km2 and by 2019–21 the glacier area reduced to 21 670 ± 292 km2, representing a total of 5.8% reduction in glacier area between 1986–89 and 2019–21. Higher glacier area loss was observed on the Barents Sea coast (7.3%) compared to the Kara (4.2%), reflecting previously observed differences in warming trends. The accuracy of the automatically generated outlines of each layer (1986–89, 2000–01 and 2019–21) was evaluated by comparing with manually corrected outlines (reference data) using random sampling, resulting in an overall accuracy estimate of between 96 and 97% compared to the reference data. This automated approach in Google Earth Engine is a promising tool for rapidly mapping glacier change that reduces the amount of time required to generate accurate glacier outlines.