the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A new global dataset of mountain glacier centerline and length
- 1College of Urban and Environmental Science, Northwest University, Xi'an 710127, PR China
- 2Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, PR China
- 3College of Geography and Environment Sciences, Northwest Normal University, Lanzhou 730070, PR China
- 1College of Urban and Environmental Science, Northwest University, Xi'an 710127, PR China
- 2Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, PR China
- 3College of Geography and Environment Sciences, Northwest Normal University, Lanzhou 730070, PR China
Abstract. Length is one of the key determinants of glacier geometry and is an important parameter of glacier inventory and modeling; glacier centerlines are crucial inputs for many glaciological applications. In this study, the centerlines and maximum lengths of global glaciers were extracted using an automatic extraction algorithm based on the latest global glacier inventory data, digital elevation data (DEM), and European allocation theory. The glacier polygons were reconstructed according to the geometric principle and an automatic checking algorithm for the global glacier outlines was designed to filter erroneous or unsupported glacier outlines. The DEMs of global glacier-covered regions were compiled using available DEMs. An updated automatic extraction tool was designed independently, and a parameterization scheme with empirical thresholds was applied for data production. The accuracy of the dataset was evaluated using random assessment with visible interpretation and comparative analysis with another dataset. The 10,764 erroneous glacier polygons, 7,174 ice caps, and 419 nominal glaciers from the Randolph Glacier Inventory (RGI) version 6.0 were identified and excluded, accounting for 8.25 % of the total. In total, 198,137 glacier centerlines were generated, accounting for 99.74 % of the total input glaciers and 91.52 % of the RGI v6.0. The accuracy of glacier centerlines was 89.68 %. The comparison between the dataset and previous datasets suggested that the majority of glacier centerlines were slightly longer than those in RGI v6.0. The extraction method of this study has a strong ability to obtain the maximum length of glaciers, meaning that the maximum lengths of some glaciers were likely underestimated in the past. The dataset constructed includes 14 sub-datasets, such as the global glacier centerline dataset, global glacier maximum length dataset, and global glacier DEM dataset, all of which can be found at link: https://doi.org/10.11922/sciencedb.01643 (Zhang and Zhang, 2022).
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Dahong Zhang et al.
Status: open (until 07 Jul 2022)
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CC1: 'Comment on essd-2022-141', Wenfeng Chen, 22 May 2022
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Just a quick look. I downloaded the shared data and checked how it performed on the Tibetan Plateau indeed, and it was good overall. But there are many large glaciers with missing centerline data, such as the Karakorum region, is there any way to compensate for this?
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RC1: 'Comment on essd-2022-141', Anonymous Referee #1, 25 May 2022
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General Comments:
Based on the glacier axis concept, Zhang et al. produced the global mountain glacier centerlines using the latest global glacier inventory and the digital elevation model data of corresponding glaciers. This research is challenging and heavy workload. The authors used the automatic checking algorithm to identify 10,764 glaciers with flawed outlines and mark the location of the defects. The centerline and related data of 198,137 worldwide mountain glaciers were automatically obtained by the compiled extraction tool, which is very important parameters for glacier research. The published datasets include not only the result data such as glacier centerline and maximum length, but also the key data such as DEM of glacier-covered and its buffer region and the glaciers of flawed outlines. The dataset has high quality, and the manuscript is generally well organized and written. The manuscript can be accepted after addressing my following comments.
Specific comments:
- The manuscript mentioned that the automatic extraction tool does not support ice caps, nominal glaciers and some glaciers of flawed outlines, which accounts for 8.48% of the total number of worldwide mountain glaciers. I think it is necessary to add more details to the manuscript, including providing data users with possible approaches calculated the centerlines of these glaciers.
- L243-L263: 100 random results for accurate evaluation in each region. Did you decide it yourself or refer to others? The number of glaciers in each region is different. Can a certain proportion be used to select centerlines, and the assessment results are possibly more convincing?
- It is suggested to move the notes in Figure 1 after the caption of Figure 1.
- L267-L271: Overall success rate or average success rate? How is it calculated?
- L305-L315: Is it necessary to list a table to better understand?
Technical corrections:
L37 Add a space after 'changes'.
L77 '; the' -> ', their'.
L124 'However' -> 'Nevertheless'.
L195 'was' -> 'are'.
L225 'a glacier' -> 'glaciers'
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RC2: 'Comment on essd-2022-141', Wang xin, 25 May 2022
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General Comments:
I carefully reviewed the manuscript of “A new global dataset of mountain glacier centerline and length” submitted by Zhang et al. In this paper, the European allocation is applied to the automatic extraction of global mountain glacier centerline, which proved to be a feasible and reasonable approach. The manuscript includes a detailed description of data production, processing method and accuracy evaluation. The dataset is publicly available and its overall quality is good, which includes 14 sub-datasets including all input, process and result data. Besides of the GGCLDS and GGMLDS, I think the shared DEM (GGEDS), which was mosaicked with each glacier regions as units, is also a reasonable choice for relevant researchers to study. Overall, the manuscript is well-written with clearly structure. I think this manuscript can be considered for publication after some minor correction and technical comments have been addressed.
Specific comments:
- According to the automatic checking algorithm for the global glacier outlines in this study, my understanding is that the glacier polygons with defects only on the Pgec are a high proportion in the FGODS, and they are probably to be supported by the automatic extraction tool. I suggest designing algorithms for this part of the FGODS to identify and repair them. The repaired glacier outlines are slightly distinguished from the RGI v6.0, so my suggestion is that their centerlines should be published as a supplementary dataset to increase the global coverage of this dataset.
- In general, the accuracy of 89.68% is acceptable for the results of fully automatic algorithm, but I am more concerned about the precautions for future readers to adopt the current dataset, the limitations of the dataset, and the possibility for improvement in the future. It is suggested to add a new chapter 4.2.3, focusing on the above problems.
- If there are the qualified glacier outlines corresponding to the glaciers in the FGODS in the future, I hope to supplement their centerlines to this dataset in time.
Technical corrections:
L74 Delete 'of'.
L108 'better' -> 'smaller'.
L120 'ASTERGDEM'-> 'ASTER GDEM'.
L208 total global mountain glaciers or total glaciers?
L362ãL488 Missing the name of horizontal axis.
Dahong Zhang et al.
Data sets
A new global dataset of mountain glacier centerline and length Dahong Zhang, Shiqiang Zhang https://doi.org/10.11922/sciencedb.01643
Dahong Zhang et al.
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