A new automatic approach for extracting glacier centerlines based on Euclidean allocation

Zhang, Dahong; Yao, Xiaojun; Duan, Hongyu; Liu, Shiyin; Sun, Meiping; Li, Dazhi

doi:10.5194/tc-15-1955-2021

Cited by 17 publications

(13 citation statements)

References 28 publications

(37 reference statements)

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“…Thus, we only consider errors resulting from the spatial resolution of satellite remote sensing images in this study, e.g., [42]. To extract the glacial centerlines, we used an automatic method proposed by Zhang et al [43] A Sentinel-2 image was used to evaluate the accuracy of these centerlines [44], the uncertainties were no more than ±23 m.…”

Section: Glacier Delineation and Glacier Centerline Extractionmentioning

confidence: 99%

The Evolution of the Glacier Surges in the Tuanjie Peak, the Qilian Mountains

Gao

Liu

et al. 2022

Remote Sensing

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Glacier surges (GSs) are a manifestation of glacier instability and one of the most striking phenomena in the mountain cryosphere. Here, we utilize optical images acquired between 1973 and 2021 to map changes in glacier surface velocity and morphology and characterize differences in surface elevation using multi-source DEMs in the Tuanjie Peak (TJP), located in the Qilian Mountains (QLMs). These data provide valuable insights into the recent dynamic evolution of glaciers and hint at how they might evolve in the next few years. We identified a confirmed surge-type glacier (STG), three likely STGs, and three possible STGs. Our observations show that TJP GSs are generally long-term, although they are shorter in some cases. During the active phase, all glaciers exhibit thickened reservoir areas and thinned receiving areas, or vice-versa. The ice volume transfer was between 0.11 ± 0.13 × 107 m3 to 5.71 ± 0.69 × 107 m3. Although it was impossible to obtain integrated velocity profiles throughout the glacier surge process due to the limitations of available satellite imagery, our recent observations show that winter velocities were much higher than summer velocities, suggesting an obvious correlation between surge dynamics and glacial hydrology. However, the initiation and termination phase of GSs in this region was slow, which is similar to Svalbard-type STGs. We hypothesize that both thermal and hydrological controls are crucial. Moreover, we suggest that the regional warming trend may potentially increase glacier instability and the possibility of surge occurrence in this region.

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Section: Glacier Delineation and Glacier Centerline Extractionmentioning

confidence: 99%

The Evolution of the Glacier Surges in the Tuanjie Peak, the Qilian Mountains

Gao

Liu

et al. 2022

Remote Sensing

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“…As an important attribute of glacier geometry, glacier length constitutes the basis for calculating the retreat and advance distance of a glacier terminal, which can well characterize the change of glaciers and is a key parameter for global glacier inventory. Based on the automatic extraction method of glaciers centerline proposed by Zhang et al (2021), we extracted the length data of surging glaciers in HMA, and took the maximum length as the statistical standard (Yao et al, 2015) to calculate the advance distance of surging glaciers.…”

Section: Glacier Length Extractionmentioning

confidence: 99%

“…The extraction accuracy of glacier length depends on the accuracy of the extracted glacier outline and the quality of DEM data. Generally, the influence of the latter on glacier length is negligible (Yao et al, 2015;Zhang et al, 2021).…”

Section: Glacier Length Extractionmentioning

confidence: 99%

Surging glaciers in High Mountain Asia between 1986 and 2021

Sun

Zhou

Yao

et al. 2022

Preprint

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Abstract. High Mountain Asia (HMA) is one of the main distribution areas of surging glaciers in the world. The glacier change represented by the Karakoram anomaly has been a topic of wide concern. Surging glaciers not only reshape the peri-glacial landscape, but may also directly or indirectly lead to disasters. Therefore, it is of great importance to understand the distribution characteristics, periodic laws, and occurrence mechanisms of surging glaciers. Based on Landsat TM/ETM+/OLI remote sensing images from 1986–2021, a total of 244 surging glaciers in HMA were identified, covering an area of 10974.25 km2, accounting for 11.25 % of the total area of glaciers in HMA. The Karakoram Range and Pamirs are the main mountain/plateau where 185 surging glaciers are more highly concentrated. Three basins, including Amu Darya, Tarim and Indus, have 208 surging glaciers comprising 85.25 % of the total amount of surging glaciers in HMA, covering an area of 10096.89 km2. From 1986–2021, these surging glaciers advanced at least 2802 times, and exhibited different temporal and spatial trends. Obvious differences exist in the surge phase and the quiescent phase of glaciers in different regions of HMA. The surge phase of surging glaciers in the Karakoram Range and Pamirs is generally short, mostly between 2~6a, the quiescent phase is 5~19a, and the surging period is 9~24a. The mechanism of surging glaciers in HMA is more complex, which is different from Svalbard and Alaska glaciers.

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“…Due to the lack of glacier velocity field data, the main flow lines cannot be obtained on a large scale. The glacier centerline, generated via the axis line method (Le Bris and Paul, 2013;Machguth and Huss, 2014;Kienholz et al, 2014;Zhang et al, 2021), is typically used to represent the main flow line. The glacier centerline is a critical parameter for analyzing the ice velocity field D. Zhang et al: A new global dataset of mountain glacier centerlines and lengths (Heid and Kääb, 2012;Melkonian et al, 2017), estimating glacier volumes (Li et al, 2012;Gao et al, 2018), and developing glacier models (Oerlemans, 1997;Sugiyama et al, 2007;Maussion et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…The tradeoff function approach of Machguth and Huss (2014), which is based on the axis concept, has been applied to almost all global mountain glaciers but excludes the centerlines of the branches of glaciers. Despite many attempts to overcome these limitations in recent years (Yao et al, 2015;Yang et al, 2016;Ji et al, 2017;Hansen et al, 2020;Xia, 2020;Zhang et al, 2021), to date, global datasets of the centerline and length of mountain glaciers are rare. Based on our recent study on successfully extracting the glacier centerline using the Euclidean allocation method (Zhang et al, 2021), we aim to combine publicly available digital elevation data into one global digital elevation model (DEM), at 30 m resolution and extending from 90 • N to 90 • S, to check and correct the global glacier outlines and obtain a new graphic dataset of the centerline and length of global mountain glaciers.…”

Section: Introductionmentioning

confidence: 99%

A new global dataset of mountain glacier centerlines and lengths

Zhang

Zhou

et al. 2022

Earth Syst. Sci. Data

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Abstract. The length of a glacier is a key determinant of its geometry and is an important parameter in glacier inventories and modeling; glacier centerlines are the lines along which the main flow of glaciers takes place and, thus, are crucial inputs for many glaciological applications. In this study, the centerlines and maximum lengths of global glaciers were extracted using a self-designed automatic extraction algorithm based on the latest global glacier inventory data, digital elevation model (DEM), and European allocation theory. The accuracy of the dataset was evaluated through random visual assessments and comparisons with the Randolph Glacier Inventory (RGI) version 6.0. A total of 8.25 % of the outlines of the RGI were excluded, including 10 764 erroneous glacier polygons, 7174 ice caps, and 419 nominal glaciers. A total of 198 137 glacier centerlines were generated, accounting for 99.74 % of the input glaciers. The accuracy of glacier centerlines was 89.68 %. A comparison between the dataset and the previous dataset suggested that most glacier centerlines were slightly longer than those in RGI v6.0, meaning that the maximum lengths of some glaciers had been likely underestimated in the past. The constructed dataset comprises 17 sub-datasets, including global glacier centerlines, maximum lengths, and DEMs, all of which can be found at https://doi.org/10.11922/sciencedb.01643 (Zhang and Zhang, 2022).

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A new automatic approach for extracting glacier centerlines based on Euclidean allocation

Cited by 17 publications

References 28 publications

The Evolution of the Glacier Surges in the Tuanjie Peak, the Qilian Mountains

The Evolution of the Glacier Surges in the Tuanjie Peak, the Qilian Mountains

Surging glaciers in High Mountain Asia between 1986 and 2021

A new global dataset of mountain glacier centerlines and lengths

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