A new global dataset of mountain glacier centerlines and lengths

Zhang, Dahong; Zhou, Gang; Li, Wen; Zhang, Shiqiang; Yao, Xiaojun; Wei, Shimei

doi:https://doi.org/10.5194/essd-14-3889-2022

Articles | Volume 14, issue 9

https://doi.org/10.5194/essd-14-3889-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Extreme environment datasets for the three poles

https://doi.org/10.5194/essd-14-3889-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 9

Data description paper

|

01 Sep 2022

Data description paper |

| 01 Sep 2022

A new global dataset of mountain glacier centerlines and lengths

Dahong Zhang, Gang Zhou, Wen Li, Shiqiang Zhang, Xiaojun Yao, and Shimei Wei

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Final revised paper (published on 01 Sep 2022)
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Preprint (discussion started on 12 May 2022)
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Interactive discussion

Status: closed

CC1:
'Comment on essd-2022-141', Wenfeng Chen, 22 May 2022

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?

Citation: https://doi.org/10.5194/essd-2022-141-CC1
- AC1: 'Reply on CC1', Dahong Zhang, 08 Jul 2022
  
  Thanks for your helpful comments to improve this manuscript.
  Comment: 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?
  Response: Thanks for your insights. Mountain glaciers on the Tibetan Plateau involve three glacier regions: Central Asia (R13), South Asia West (R14), and South Asia East (R15). The dataset has 95.73% (91455/95536) coverage in High Asia (R13, R14 and R15). The glaciers that are not provide centerlines are mainly 1545 ice caps in R13 and 1946 defect glaciers in R14. Almost all glaciers in the Karakorum region are in R14, but the glacier outlines of R14 in the RGI v6.0 rely on automated extraction algorithm and they are generally jagged and have geometric flaws.
  In the recent version of this dataset (https://doi.org/10.11922/sciencedb.01643), prioritizing the coverage of this dataset, we designed a geometry-based algorithm to repair FGODS and provided data users with 10676 centerlines of these glaciers in the form of supplementary dataset. Corresponding codes and results see sub-datasets CODES and SUP_220707. After the update, the coverage of this dataset in the mountain glaciers of High Asia has increased from 95.73% to 97.78%, and coverage in the R14 has increased from 92.12% to 99.01% (27711/27988). Unfortunately, nominal glaciers and ice caps still lacks the qualified sources of glacier outlines to calculate their centerlines.
  For some glaciers that are not provided centerlines in this dataset, data users need to update the corresponding glacier outlines and use the automatic extraction tool provided in this study to generate their centerlines, which involves the defective glacier outlines (FGODS), nominal glaciers and ice caps of RGI v6.0. The FGODS and nominal glaciers are easy to generate centerlines as long as there are correct glacier outlines. However, automatic approaches dividing ice caps from glacial complexes into individual glaciers are currently limited, and data users only can use own criterion to divide ice caps and then use our tool to generate centerlines.
  
  Citation: https://doi.org/10.5194/essd-2022-141-AC1
RC1:
'Comment on essd-2022-141', Anonymous Referee #1, 25 May 2022
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'
Citation: https://doi.org/10.5194/essd-2022-141-RC1
- AC2: 'Reply on RC1', Dahong Zhang, 08 Jul 2022
  
  Dear reviewer #1,
  Please find attached our response.Thanks for your helpful comments to improve this manuscript, and we will be very glad to receive your feedback.
  Yours sincerely,
  Dahong Zhang, Gang Zhou, Wen Li, Shiqiang Zhang *, Xiaojun Yao, and Shimei Wei
  
  Citation: https://doi.org/10.5194/essd-2022-141-AC2
RC2:
'Comment on essd-2022-141', Wang xin, 25 May 2022
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 and , I think the shared DEM (), 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 _gec are a high proportion in the , and they are probably to be supported by the automatic extraction tool. I suggest designing algorithms for this part of the 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 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.
Citation: https://doi.org/10.5194/essd-2022-141-RC2
- AC3: 'Reply on RC2', Dahong Zhang, 08 Jul 2022
  
  Dear Prof. Wang,
  Please find attached our response. Thanks for your helpful comments to improve this manuscript, and we will be very glad to receive your feedback.
  Yours sincerely,
  Dahong Zhang, Gang Zhou, Wen Li, Shiqiang Zhang *, Xiaojun Yao, and Shimei Wei
  
  Citation: https://doi.org/10.5194/essd-2022-141-AC3

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Dahong Zhang on behalf of the Authors (13 Jul 2022) Author's response Author's tracked changes Manuscript

ED: Publish subject to minor revisions (review by editor) (29 Jul 2022) by Min Feng

I would like to thank the authors for submitting the revision, which I believe has addressed the previous review comments. However, there are still many ill-expressions and confusing sentences in the manuscript. I think that the authors need to carefully check and improve the writing of the manuscript before it is accepted for publication. I would also encourage the authors to ask for help from native English speakers or language professionals.

A few specific comments and suggestions:

The current Abstract is a bit flat and lengthy; I would suggest the authors revise the Abstract to be concise and highlight the most important conclusions of the work.

Line 69-74, are these three types of methods or three methods? Please be consistent.

Line 75, what does “complex glaciers” refer to?

Line 82-83, “including that of …” is confusing.

Line 85, 30 m -> 30-m

In figure 1, some regions on the map were not mentioned in the caption, such as R04.

Line 104, I do not think “preliminary” is a proper term for describing these DEM data efforts.

Line 107, “modernization” is confusing. The SRTM is not the most up-to-date DEM.

Lien 142, “unknown projection coordinate system” is a confusing description. Does it mean the data is not usable?

Figure 3, would it be helpful to add satellite images for the regions for reference?

Line 182, “incorrect glacier outline” is confusing.

Lien 192-194, Line 199, Line 226, the sentences are confusing.

Line 295, What does “All data” refers to?

Line 233, Please disclose the full definition of the projection instead of referring to it as “user-defined”.

Line 234, is confusing.

Line 240, clarify “key associated data”.

Line 242, clarify “failed glacier outlines dealt”.

Line 247, the 19 samples were confusing. Collecting 19 samples in each of the 100 glaciers?

Line 270, what “other model parameters”?

In figure 5, the labels in the legend do not consistent with the labels on the map.

Line 349, please confirm that “-9” is the correct value here.

Line 354, “histogram statistics”?

Line 388, “the results” refers to which results?

Line 390-394, the sentence is confusing.

In figure 7, please add a legend for the colors of the DEM.

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AR by Dahong Zhang on behalf of the Authors (12 Aug 2022) Author's response Author's tracked changes Manuscript

ED: Publish as is (15 Aug 2022) by Min Feng

AR by Dahong Zhang on behalf of the Authors (15 Aug 2022)

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Short summary

The length of a glacier is a key determinant of its geometry; glacier centerlines are crucial inputs for many glaciological applications. Based on the European allocation theory, we present a new global dataset that includes the centerlines and lengths of 198 137 mountain glaciers. The accuracy of the glacier centerlines was 89.68 %. The constructed dataset comprises 17 sub-datasets which contain the centerlines and lengths of glacier tributaries.