Freeze-Thaw Deformation Cycles and Temporal-Spatial Distribution of Permafrost along the Qinghai-Tibet Railway Using Multitrack InSAR Processing

Round 1

Reviewer 1 Report

The paper present MT-InSAR data in Qing-hai-Tibet Railway in order to identify the areas affected by subsidence related to the melting of permafrost. Authors describe in detail their results through multiple tracks but they fail in creating an interesting paper for the international audience. First, authors describe vaguely their study area. Second, there are many repetitions in the descriptions both regarding the used terms and regarding the text structure. In other words, they repeat many words innecesary and use the same structure in several paragraphs. Third, "Section 4.2" seems more like a report chapter than a section of a scientific paper. Forth, the manuscript is not well structured and it is confuse in many parts. Fith, figures are not clear for the readers who are unfamiliar with the study area. Sixth, the English is correct or almost understandable but it also needs a revision. Seventh, the innovative aspects of the research are not clear enough. I think that all these points describe perfectly the drawbacks of the manuscript. Forthermore, some authors have already published similar papers (Wang et al., 2017, 2018; Zhang et al., 2019a,b, 2020) and I do not see any sustancial innovation in this new research. For this reason, I think that the manuscript deserve to be rejected.

I encourage authors to follow these recommendations to improve the quality of the paper:
1. Describe more in detail the study area. Readers need to understand very well the setting to interpret the next sections.
2. Focus your description in the most compelling issues observed in the data.
3. Include annotations in the Google Earth images to help readers in their interpretation. Use also geomorphological maps where they are available to support your observations.
4. Edit the style of the English and the structure of the text.
5. Find the aspects that make the research or the results innovative and interesting for the International audience.

References:

Wang, C., Zhang, Z., Zhang, H., Wu, Q., Zhang, B., & Tang, Y. (2017). Seasonal deformation features on Qinghai-Tibet railway observed using time-series InSAR technique with high-resolution TerraSAR-X images. Remote Sensing Letters , 8(1), 1–10.

Wang, C., Zhang, Z., Zhang, H., Zhang, B., Tang, Y., & Wu, Q. (2018). Active Layer Thickness Retrieval of Qinghai–Tibet Permafrost Using the TerraSAR-X InSAR Technique. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(11), 4403–4413.

Zhang, X., Zhang, H., Wang, C., Tang, Y., Zhang, B., Wu, F., Wang, J., & Zhang, Z. (2019a). Time-Series InSAR Monitoring of Permafrost Freeze-Thaw Seasonal Displacement over Qinghai–Tibetan Plateau Using Sentinel-1 Data. Remote Sensing, 11(9), 1000.

Zhang, X., Zhang, H., Wang, C., Tang, Y., Zhang, B., Wu, F., Wang, J., & Zhang, Z. (2020). Active Layer Thickness Retrieval Over the Qinghai-Tibet Plateau Using Sentinel-1 Multitemporal InSAR Monitored Permafrost Subsidence and Temporal-Spatial Multilayer Soil Moisture Data. IEEE Access, 8, 84336–84351.

Zhang, Z., Wang, M., Wu, Z., & Liu, X. (2019b). Permafrost Deformation Monitoring Along the Qinghai-Tibet Plateau Engineering Corridor Using InSAR Observations with Multi-Sensor SAR Datasets from 1997-2018. Sensors , 19(23). https://doi.org/10.3390/s19235306

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

The paper shows the results obtained in the measurement of ground movements in an area affected by permafrost (Qinghai-Tibet Railway). For this, it uses Differential Interferometry techniques together with a linear and seasonal model to detect those areas affected by seasonal movements. This approximation depends on a series of measurements of the study area that are difficult to obtain, especially at the spatial resolution level. At a methodological level, I believe that the article should be modified for a better understanding, and especially validation of the results obtained. Below I detail a series of points that must be improved:

1. The sentence between lines 67 and 72 must be rewritten as it is not understood.

2. Why have ascending and descending orbits not been used? This could better cover the ground due to geometric distorting effects, such as layover. In addition, the vertical and horizontal (East-West) components of the movement could be obtained.

3. Explain the c component in equation (4).

4. Define SVD (Single Value Decomposition) in line 210.

5. I would reduce the number of examples, since it is not a result report, but a scientific publication, and it is not necessary to repeat a series of concepts that appear in the different areas.

6. A "linear + seasonal" model is being used that depends on a series of variables that are difficult to find in most areas. It should be shown in the publication results obtained using a PSI technique without model restrictions, to later detect those patterns with seasonal behavior. In this way, the data would not be forced and the results would be more reliable. In addition, this comparison will give more credibility to the model presented.

7. For the validation of the results, the leveling measures must be projected to LOS, and not vice versa, since the projection of LOS to vertical is an approximation.

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

The paper contains an in-depth analysis of the seasonal deformation along the QTR railway in China. The methodology used is based on the parameterization of the terrain motion due to permafrost freeze-thaw cycling with a composite model based on ground motion measurements, local air temperatures, and geotechnical parameters.  This methodology was well published in 2018 [52] when it was satisfyingly tested with GPS on a site in Alaska.

This methodology is now used on QTR by extracting the ground motion measurements from Sentinel 1 InSAR and again using the local surface temperatures (meteo data source not given).  This parameterization allows to expand the analysis to an extremely vast area exploiting 2.3 TB of SAR data. A detailed analysis of the behaviour of permafrost seasonal deformation and progressive ground motion is then carried out, for different locations along the profile. Systematically, Google Earth images are provided, to explain the local behaviour of the deformation.

The chosen parameterization allows to obtain significant results on a vast area.

 

To my opinion, the results are quite convincing. The paper is very clearly written and I think that it can be published as it is.

 

Typos

Line 17 and other 105 10^5

Line 177 n – factors not explained, do as in [52]

Line 229 Small square …. least squares

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Thank you for applying the required improvements to the paper, so that it can be published on a technical level. However, before publication, the text should be checked for spelling and grammar.

Author Response

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Author Response File: Author Response.docx