Round 1

Reviewer 1 Report (Previous Reviewer 3)

Dear Authors,

after the reorganization of the manuscript and the major revision made, I suggest publication after minor revision. Find my comments in the attached pdf.

Your sincerely

Comments for author File: Comments.pdf

Author Response

Manuscript Number: remotesensing-2407150

 

Response to comments

We would like to thank the editor and reviewers for their valuable suggestions on our manuscript entitled “An efficient method for continuous track monitoring in regions of differential land subsidence rate using the integration of PS-InSAR and SBAS-InSAR” (Manuscript Number: remotesensing-2407150). We have studied the comments carefully and have made corrections which we hope to meet with approval. Revised portions are marked in red in the manuscript. Specific responses to the comments are also detailed below.

Thanks for all the help.

Best regards,

Corresponding Author: Shuangfeng Guo

 

Response to the reviewer’s comments:

 

Reviewer 1#:

After the reorganization of the manuscript and the major revision made, I suggest publication after minor revision. Find my comments in the attached pdf.

Response: First of all, we really appreciate your hard work and valuable comments on our manuscript. All of these comments are positive and constructive. We thank the reviewer for acknowledging the worthiness of the work. We have carefully read the review report and reply each comment seriously. The replies are as follows:

 

Reviewer_Comment_1: I recommend you to improve the resolution of the image. It's hard to read the flow chart in Fig. 1.

Response: Thanks for the reviewer’s comments. We totally agree with your viewpoints. As the Reviewer’s constructive advice, we have modified Fig. 1 in the revised manuscript. (The modified figure also has been updated in the revised manuscript)

 

Reviewer_Comment_2: I suggest you format all the Y and N the same way in Fig. 2.

Response: Thanks very much for this constructive comment on this figure. We agreed with the reviewer and have modified all the Y and N in the same way in Fig.2.  (The modified figure also has been updated in the revised manuscript)

 

Reviewer_Comment_3: As previously stated, there should be a bibliographic reference relating to the geology of the study area.

Response: Thanks for the reviewer’s comments on this issue. We agreed with the reviewer and have added the reference in this section according to the suggestion of the reviewer.

Now the modified texts read as follows:

Page 10, lines 239-247:

           The research region is the western region of the Qinhuai River, Nanjing City, Jiangsu Province, China, which is located southwest of Nanjing’s main city, with the Qinhuai River, the South River, the Qinhuai New River, the Yangtze River, and the Sancha River to the southeast and northwest, respectively, and a land area of 56 km², as seen in Fig. 3. In the past decade, the accelerated urbanization of this research region has triggered regional ground deformation, and the differences in geological units, structural forms, and construction disturbances have caused drastic differences in ground deformation [51]. The LOS deformation from the tracks should be projected to the vertical. Meanwhile, considering the flat topography of the plain in this case study, the displacements obtained from InSAR (along the LOS direction) are directly interpreted as vertical deformations in this study.

51. 51. Yang Z.; Xu J. Monitoring the land subsidence in Hexi area of Nanjing by using Sentinel-1A. Bulletin of Surveying and Mapping, 2020, 0(1): 61-65, 75.

 

Reviewer_Comment_4: Image resolution is still poor in Fig.5.

Response: Thank you for your valuable comments on this figure. We totally agreed with the reviewer. The figure has been modified to make it clearer according to the comment of the reviewer. (The modified figure also has been updated in the revised manuscript)

 

Reviewer_Comment_5: “Jiangdong Road and south of Mochou Lake......”Where are these locations? If you name them, you have to show them in the images.

Response: Thank you for your praiseworthy comments on our manuscript. We totally agreed with the reviewer and have corrected Fig.7 in this manuscript. (Now the modified figure has been displayed in the revised manuscript)

 

Reviewer_Comment_6: I suggest to describe (a) and (b) in the caption, inserting (a) and (b) in the respectevely images. Development of accelerated subsidence areas: (a)...; (b)...in Fig.10.

Response: Thanks very much for pointing out this issue. We agreed with the comment of the reviewer. We apologize for the confusion and inappropriateness of the subtitle with each other. Some modifications have been done to make this issue easier to understand according to the comment of the reviewer. (The modified figure also has been updated in the revised manuscript)

 

Reviewer_Comment_7: Image resolution is still poor in Fig.12.

Response: Thanks very much for this constructive comment. Thanks for pointing out the confusing figures. We agree with the comment of the reviewer. We are very sorry for the poor resolution. We have redrawn these sentences to improve the resolution in our revised manuscript now. (The modified figure also has been updated in the revised manuscript)

 

Reviewer_Comment_8: Section 6 and 7 have the same name. I suggest you to insert a 6.3 section "general remarks" for example or something similar.

Response: Thank you so much for your precious suggested studies. We are very sorry for the wrong expression of this section. It has been modified in the revised manuscript according to the suggestion of the reviewer (This revision had been updated in the revised manuscript). 

  

        In addition, we have tried our best to revise the English and the technical aspect of the whole manuscript carefully. We also asked the English writing center and the native speaker Dr. Ed Holroyd who is skilled in English to help us with checking the English writing and Grammar. Meanwhile, we have submitted this study to the English language editing from the MDPI institution to polish the whole manuscript (Please see the certificate posted at the end of this document). We hope that the English is now acceptable for the next review process. The technical content aspect of this paper has been revised and checked by Professor who is very proficient in remote sensing monitoring technology. Special thanks to you for your good comments.

 

       We tried our best to improve the manuscript according to the reviewers’ comments. These changes will not influence the main content and conclusions of the paper. Here, we did not list all the changes but marked them in red in the revised paper. We sincerely appreciate the Editors/Reviewers’ great efforts and kind help. Hope that these corrections will meet the standard of the journal.

Thank you again for your time and effort, and for helping us improve the manuscript.

 

Yours Sincerely,

Peng Zhang; Xiaqing Qian; Shuangfeng Guo*; Bikai Wang; Jin Xia; Xiaohui Zheng

Author Response File: Author Response.pdf

Reviewer 2 Report (Previous Reviewer 2)

The reviewer appreciates the authors' effort in responding to the reviewer's comments and suggestions. The paper has significantly improved from its previous version. Some minor comments and suggestions are listed below.

Point 1: In line 6 of the abstract and line 66 of the introduction, kindly change 'Selforganizing' to 'Self-Organizing'.

Point 2: Avoid using bold text for Figure 1 and other figures' x-y axes (e.g., geographical coordinates. Authors are also recommended to ensure that all figures' legends and labels are legible.

Point 3: In Figure 15, the reviewer suggests including the subsidence rate color scheme.

Point 4: The reviewer suggests including a plausible explanation why the authors only processed the ascending dataset and regarding the velocity model used.

Moderate editing of the English language. Carefully proofread the manuscript.

Author Response

Manuscript Number: remotesensing-2407150

 

Response to comments

We would like to thank the editor and reviewers for their valuable suggestions on our manuscript entitled “An efficient method for continuous track monitoring in regions of differential land subsidence rate using the integration of PS-InSAR and SBAS-InSAR” (Manuscript Number: remotesensing-2407150). We have studied the comments carefully and have made corrections which we hope to meet with approval. Revised portions are marked in red in the manuscript. Specific responses to the comments are also detailed below.

Thanks for all the help.

Best regards,

Corresponding Author: Shuangfeng Guo

 

Response to the reviewer’s comments:

 

Reviewer 2#:

The reviewer appreciates the authors' effort in responding to the reviewer's comments and suggestions. The paper has significantly improved from its previous version. Some minor comments and suggestions are listed below.

First of all, we would like to express our heartfelt thanks for your precious comments on our manuscript. All of them are constructive and encouraging. We have learned much from them. We have learned much knowledge from them and done a more in-depth literature review to meet the Reviewer’s comments.

 

Reviewer_Comment_1: Point 1: In line 6 of the abstract and line 66 of the introduction, kindly change 'Selforganizing' to 'Self-Organizing'.

Response: Thanks for the reviewer’s comments on this word. We agreed with the Reviewer and have corrected these issues in the Abstract.

Now the modified texts read:

Page 1, lines 25-27:

Based on PS-InSAR processing, the Iterative Self-Organizing Data Analysis Techniques (ISODATA) algorithm is adopted to search the boundary of differential subsidence between slow and fast subsidence rates.

 

Reviewer_Comment_2: Point 2: Avoid using bold text for Figure 1 and other figures' x-y axes (e.g., geographical coordinates. Authors are also recommended to ensure that all figures' legends and labels are legible.

Response: Thank you for your praiseworthy comments on Figure 1 and other figures' x-y axes. As per the Reviewer’s good instructions, we totally agreed with the reviewer and have redrawn Fig.1 carefully according to the comments of the reviewer (This revision had been updated in Section 2.2.).

 

Reviewer_Comment_3: Point 3: In Figure 15, the reviewer suggests including the subsidence rate color scheme.

Response: Thank you for your valuable comments on Figure 15. We are very sorry for the missing identification, which makes the figure confusing. Figure 15 has been modified to make it easier to read according to the comment of the reviewer (Now the modified figure has been displayed in the revised manuscript).

 

Reviewer_Comment_4: The reviewer suggests including a plausible explanation why the authors only processed the ascending dataset and regarding the velocity model used.

Response: Thank you for your praiseworthy comments on this issue. The reviewer pointed out that only the ascending dataset was processed in this study, we agreed with the reviewer.

Firstly, because the orbital information, satellite view, and radar reflection area are different between the ascending and descending datasets, using both ascending and descending datasets will be detrimental to the formation of interference fringes and increase interference errors.

Secondly, based on the study area and the period of data collection, a comparison of the ascending and descending dataset reveals that the main parameters and time series of the ascending data set are more complete.

Thirdly, the main aim of this paper focuses on the new land subsidence monitoring method of integrating PS-InSAR and SBAS-InSAR by data fusion of different interferometry in differential subsidence rates according to the respective reliability of PS-InSAR and SBAS-InSAR to different radar reflection features. The SAR dataset acquired by ascending Sentinel-1 satellite is sufficient to demonstrate the advantages of the proposed method in this paper, therefore, we did not choose the descending Sentinel-1 satellite, which will be considered in the next research according to the great suggestion of the reviewer.

 

In addition, we have tried our best to revise the English and the technical aspect of the whole manuscript carefully. We also asked the English writing center and the native speaker Dr. Ed Holroyd who is skilled in English to help us with checking the English writing and Grammar. Meanwhile, we have submitted this study to the English language editing from the MDPI institution to polish the whole manuscript (Please see the certificate posted at the end of this document). We hope that the English is now acceptable for the next review process. The technical content aspect of this paper has been revised and checked by Professor who is very proficient in remote sensing monitoring technology. Special thanks to you for your good comments.

 

We tried our best to improve the manuscript according to the reviewers’ comments. These changes will not influence the main content and conclusions of the paper. Here, we did not list all the changes but marked them in red in the revised paper. We sincerely appreciate the Editors/Reviewers’ great efforts and kind help. Hope that these corrections will meet the standard of the journal.

Thank you again for your time and effort, and for helping us improve the manuscript.

 

Yours Sincerely,

Peng Zhang; Xiaqing Qian; Shuangfeng Guo*; Bikai Wang; Jin Xia; Xiaohui Zheng

Author Response File: Author Response.pdf

Reviewer 3 Report (New Reviewer)

In the case of land subsidence, there are vertical displacements. Using only one orbit, you get LOS displacement. Subsidence is not the same as LOS displacement. Please correct this throughout the article.

Please supplement the introduction with a literature review in the field of used e.g. ISBAS, DS-InSAR etc.\

Table 1. How were the ranges of subsidence assumed for development areas? For what purpose was cumulative subsidence compiled?

Line 240 Why did you only use 38 radarograms. Approximately 90 are available for this region and data frame (S1A IW SLC, orb. 69, frame 99; based on asf.alaska website)

A very short discussion. Please refer to other research results and compare/comment them in the context of the presented results.

What is the increase in accuracy compared to classic PSI? What about computational time?

Author Response

Manuscript Number: remotesensing-2407150

 

Response to comments

We would like to thank the editor and reviewers for their valuable suggestions on our manuscript entitled “An efficient method for continuous track monitoring in regions of differential land subsidence rate using the integration of PS-InSAR and SBAS-InSAR” (Manuscript Number: remotesensing-2407150). We have studied the comments carefully and have made corrections which we hope to meet with approval. Revised portions are marked in red in the manuscript. Specific responses to the comments are also detailed below.

Thanks for all the help.

Best regards,

Corresponding Author: Shuangfeng Guo

 

Response to the reviewer’s comments:

 

Reviewer 3#:

Reviewer_Comment_1: In the case of land subsidence, there are vertical displacements. Using only one orbit, you get LOS displacement. Subsidence is not the same as LOS displacement. Please correct this throughout the article.

Response: Thank you for your constructive comment on this issue. We are sorry for the ambiguous expressions of this important section in our manuscript. As per the Reviewer’s good instructions, we totally agreed with the reviewer and have carefully corrected this issue and added some sentences to clear this question according to the comments of the reviewer (This revision and supplement sentences have been updated throughout the revised manuscript).

 

Reviewer_Comment_2: Please supplement the introduction with a literature review in the field of used e.g. ISBAS, DS-InSAR etc.

Response: Thanks very much for this constructive comment. We agreed with the reviewer. The literature review in the field of ISBAS or DS-InSAR has been supplemented according to the comment of the reviewer. (The updated references have been supplemented in the revised manuscript)

Now the added sections read as below:

Page 2, lines 52-69:

Interferometric Synthetic Aperture Radar (InSAR) is a powerful technique for extracting information related to ground deformation, which is an effective method for measuring land subsidence by exploring data archives that allow us to study the past, with all-weather and day/night imaging capability, a wide range of spatial coverages, extremely high spatial-temporal resolutions, and remote access to data [12-17]. Differential InSAR (D-InSAR) utilizes the temporal baseline to monitor the ground deformation and to estimate such small deformation. However, the accuracy of D-InSAR measurement results is very sensitive to spatial-temporal decorrelation and is always affected by the and atmospheric delay [18-19]. To solve this problem, time-series InSAR techniques are widely employed in the monitoring of surface deformation. The persistent scatter (PS-InSAR) technique [20-22] and Small Baseline Subset InSAR (SBAS-InSAR) technique [23-28] are the principal time-series InSAR analysis used for the continuous monitoring of land subsidence. On the one hand, SBAS is the typical method of DS interferometry (DSI) [29], which attenuates the influences of decorrelation by selecting interferograms with short temporal and spatial baselines. On the other hand, Intermittent SBAS (ISBAS) is applied to minimize the decorrelation influences [30-31].

As an accurate deformation observation method, PS-InSAR enables continuous monitoring within a multi-image framework that analyzes spatial-temporal development. For improving the accuracy of slow ground deformation monitoring and high coherence of those persistent scatterers, PS-InSAR is not limited by the temporal and spatial baselines and can observe deformation over large ranges or long periods with the accumulation of large amounts of data [32-34].

 

Reviewer_Comment_3: Table 1. How were the ranges of subsidence assumed for development areas? For what purpose was cumulative subsidence compiled?

Response: Thank you so much for your precious suggested studies. We agreed with the reviewer on this viewpoint. As per the Reviewer’s good instructions, we have revised the criteria for fast- and slow-subsiding regions and Table 1 to make the ranges of subsidence easier to understand according to the comment of the reviewer.

Now the modification has been made as follows:

Page 7, lines 187-194:

The ground settlement rate classification is an important basis for designing ground settlement monitoring networks and selecting ground settlement prevention methods. The principle of classifying strong and weak areas in this paper is that if the annual average settlement rate is less than 10 mm·a^-1, the area is classified as a weakly developed area of ground settlement, if the annual average land subsidence rate is between 10 and 30 mm·a^-1, the area is defined as a moderately developed area of ground settlement, and if the annual average land subsidence rate is≥30 mm·a^-1, then the area is categorized as a strongly developed area of ground settlement, as listed in Table 1. (Now the modified Table has been displayed in the revised manuscript)

 

Reviewer_Comment_4: Line 240 Why did you only use 38 radiograms? Approximately 90 are available for this region and data frame (S1A IW SLC, orb. 69, frame 99; based on asf.alaska website)

Response: Thank you for your valuable comments on our paper. We agree with the reviewer that 38 images of Sentinel-1A data in this study area from June 2017 to July 2020 are selected for the InSAR process by SARscape software in this paper.

According to the scope of the study area and the research object of this paper, several hundred SAR image data were selected for the analysis period, spanning 4 years. Firstly, because the selection of radar images required images containing the entire study area of the paper to be effective, approximately 38 images out of more than 90 or even several hundred radar images were available radar images, with the remainder missing a portion of the study area of this paper to varying degrees. Secondly, to improve image quality and accurate InSAR analysis, the data set with higher quality SAR images in 4 years was selected for analysis. Therefore, 38 images were selected from the Sentinel-1A data set in this paper.

 

Reviewer_Comment_5: A very short discussion. Please refer to other research results and compare/comment them in the context of the presented results.

Response: Thank you so much for your precious suggestions on this study. We agreed with the comment of the reviewer. We apologize that the authors didn’t consider comparisons with other research results. We really appreciate your suggestion and have added the discussion in the Discussion section to make the research of this manuscript more comprehensive. 

Some supplementary explanations and modifications have been added to make this issue easier to understand according to the comment of the reviewer. (The supplement references have been updated in the revised manuscript)

Now, these added texts express as follows:

Pages 21-23, lines 429-463:

The numbers of PSCs and SDFPs in the fast-subsidence regions are shown in Table 6. In the regions with rapid subsidence rates, there are 4036 low-quality and low-density PSCs and 15667 updated SDFPs. Simultaneously, the density of monitoring points increased from 711/km² to 2760/km², an increase of 288.2%. In other regions, because of the low ground subsidence rate and high feature coherence, the density of existing PS points meets the demands of high precision of land subsidence monitoring. The data fusion results in the more rational deployment of monitoring points, thus significantly increasing the density of monitoring points in areas of accelerated subsidence and precluding misclassified uplift monitoring points. The method in this paper makes full use of all satellite observations while improving monitoring efficiency, enabling the timely capturing of accelerated subsidence areas within strongly developed ground settlement areas and the continuous monitoring of accelerated subsidence areas.

Even though the PS-SBAS integration results in this study are encouraging, a large error of more than 1 cm/year still occurs in certain regions of the research region. The results from existing continuous GPS stations in these regions may reduce these large errors. The concept is to model atmospheric delays using continuous GPS measurements and subsequently apply the GPS measurements to regulate the atmospheric impacts within radar interferograms. (Now the modified Table 6 has been displayed in the revised manuscript)

6.3. Induced causes of land subsidence

Many prior studies have adequately documented the exploration of land subsidence and the triggering factors in Southeast regions of China, they also lie in the southern part of Jiangsu Province, around the lower reaches of the Yangtze River, and east of Shanghai City. These regions have various types of groundwater, an uneven distribution of groundwater, and complex burial conditions, with distinctive regional characteristics. It was found that the Suzhou-Wuxi-Changzhou area has suffered severe land subsidence due to long-term excessive exploitation, ground fissure activity, and pumping [56, 57]. Based on long-term measurement data, the uneven land subsidence and the differential settlement of infrastructure in Shanghai were caused by groundwater exploitation and artificial recharge in an alternated multi-aquifer-aquitard system [58]. In most cases, the pattern of land subsidence might be even more complicated when it is induced by a combination of multiple factors at different scales. This paper focused on groundwater exploitation and the industry or underground construction, along with the effects on the spatio-temporal changes of groundwater exploitation and ground displacements. However, considering the complexity of the land use and the geological conditions in different districts of Nanjing City, the land subsidence may not be only induced by groundwater extraction and surface construction, but also by the integrated factors of numerous natural situations and anthropogenic processes. Therefore, future work should include a more comprehensive analysis of triggering factors to remove some of the limitations of this study.

 

Reviewer_Comment_6: What is the increase in accuracy compared to classic PSI? What about computational time?

Response: Thank you so much for your precious suggested studies. We would like to confirm that the density improvement of monitoring points is one of the most significant manifestations of improving the monitoring accuracy of land subsidence. In this manuscript, the data fusion method in our paper considers the high-density zone of PSCs with higher-order coherence PS-InSAR results as a complemented correction to the high-density zone of SDFP pixels SBAS-InSAR results. The data fusion of the combined field is more representative of overall subsidence characteristics than the PS-InSAR-only or SBAS-InSAR-only results, and it is better suited for the assessment of the impact of land subsidence over the study area.

We entirely agree with your suggestions that there is more work should be done to the improvement of monitoring accuracy, and we will continuously do more research to illustrate this issue in future studies.

The main aim of this paper focuses on the new land subsidence monitoring method of integrating PS-InSAR and SBAS-InSAR by data fusion of different interferometry in differential subsidence rates according to the respective reliability of PS-InSAR and SBAS-InSAR to different radar reflection features. The method is not much better in terms of computation time, which is related to the configuration of the computer and CPU and so on and is not a major consideration in this paper. As the reviewer’s good suggestion, the computation time will be considered in the next research to improve the computational efficiency.

Now the revised sentences read as follows:

Page 21, lines 429-438:

The numbers of PSCs and SDFPs in the fast-subsidence regions are shown in Table 6. In the regions with rapid subsidence rates, there are 4036 low-quality and low-density PSCs and 15667 updated SDFPs. Simultaneously, the density of monitoring points increased from 711/km² to 2760/km², an increase of 288.2%. In other regions, because of the low ground subsidence rate and high feature coherence, the density of existing PS points meets the demands of high precision of land subsidence monitoring. The data fusion results in the more rational deployment of monitoring points, thus significantly increasing the density of monitoring points in areas of accelerated subsidence and precluding misclassified uplift monitoring points. The method in this paper makes full use of all satellite observations while improving monitoring efficiency, enabling the timely capturing of accelerated subsidence areas within strongly developed ground settlement areas and the continuous monitoring of accelerated deformation areas.

 

      In addition, we have tried our best to revise the English and the technical aspect of the whole manuscript carefully. We also asked the English writing center and the native speaker Dr. Ed Holroyd who is skilled in English to help us with checking the English writing and Grammar. Meanwhile, we have submitted this study to the English language editing from the MDPI institution to polish the whole manuscript (Please see the certificate posted at the end of this document). We hope that the English is now acceptable for the next review process. The technical content aspect of this paper has been revised and checked by Professor who is very proficient in remote sensing monitoring technology. Special thanks to you for your good comments.

 

 

    We tried our best to improve the manuscript according to the reviewers’ comments. These changes will not influence the main content and conclusions of the paper. Here, we did not list all the changes but marked them in red in the revised paper. We sincerely appreciate the Editors/Reviewers’ great efforts and kind help. Hope that these corrections will meet the standard of the journal.

Thank you again for your time and effort, and for helping us improve the manuscript.

 

Yours Sincerely,

Peng Zhang; Xiaqing Qian; Shuangfeng Guo*; Bikai Wang; Jin Xia; Xiaohui Zheng

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report (New Reviewer)

Dear authors,

thank you for taking my comments into account and for your extensive replies to them.

I recommend the article in its current form for publication.

Best regards

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

1. Through the integration of PS-InSAR and SBAS-InSAR, this article aims to study an efficient method for continuous track monitoring in regions of differential land subsidence rate. The result of a case study in the article indicates that the density of monitoring points in the fast-subsidence region has greatly improved, increasing from 711 points/km² to 2760 points/km²—an increase of 288.2%, but the result of land subsidence monitoring in regions of differential land subsidence rate are not shown clearly and directly in this paper. An increase of density of monitoring points is supposed to improve the accuracy of land subsidence monitoring theoretically, but how this proposed method working on monitoring ground subsidence efficiently should be shown and proved based on the title of the article.

2. In this article, the ISODATA algorithm is adopted to define the boundary between the slow and the fast rates of the subsidence region. The land subsidence area division is the base for the follow-on study. But the division principle used for the experiment is inconsistent with the standard DZ/T 0286-2015 of the Chinese Geological and Mineral Industry mentioned in the article. The inconsistent reason has to be discussed, and the division principle used has to be explained, meanwhile, the validity of area division should be discussed. 

Other modification suggestions：

(1) Line 104, one word in this line is misspelled: ‘formulae’.

(2) Line 257, the reference to the figure in this line is wrong: the correct reference is figure 4 and figure 6.

(3) Line 278, the title of figure 8 needs to be modified: figure 8 shows the correlation between PSCs and SDFPs, not the correlation between PS and SBAS.

(4) Line 295-299, the value used for analysis here is the average annual dependency rate deviation, so the data analyzed here should be the average annual subsidence rate deviation, not the cumulative land subsidence monitoring value deviation.

 

Reviewer 2 Report

The reviewer appreciates the authors' work concerning the application of time-series InSAR techniques. Below are the comments and suggestions of the reviewer.

Point 1: In line 5 of the abstract, kindly define PS-InSAR as 'Persistent Scatterer InSAR'. In line 6 of the abstract, kindly replace 'Subsets' with 'Subset'.

Point 2: The reviewer strongly suggests revising the last two sentences of the abstract. Provide 2–3 sentences concerning the study's results and 1-2 sentences concerning the conclusion.

Point 3: In line 35 of the introduction, kindly remove reference 35 or re-order the reference list (i.e., make reference 35 reference 20) so that the reference citation is orderly observed.

Point 4: From lines 74 through 77 of the introduction, the reviewer strongly suggests not providing results. Kindly remove or revise this sentence.

Point 5: In line 88, kindly define 'DEM' as a 'digital elevation model'. The reviewer reminds the authors to define all acronyms during their first appearance and use them consistently throughout the text.

Point 6: In line 95, the reviewer suggests using either ADI or DA to represent the amplitude dispersion index. Also, what ADI values were used for the PS-InSAR and SBAS-InSAR analyses?

Point 7: The reviewer strongly suggests that equations 1 and 4 be merged. These two equations are similar and are calculated differently using various time-series InSAR implementations.

Point 8: Why did the authors only use the SAR dataset acquired by the ascending Sentinel-1 satellite? What about the SAR dataset acquired by the descending Sentinel-1 satellite?

Point 9: The authors mentioned that Sentinel-1 satellites regularly acquire SAR images over the study region (i.e., with 12 days revisit period). The reviewer is curious why there were only 38 SAR images collected for an almost 4-year analysis period. Also, if there were 38 SAR images collected, there should be 37 interferometric pairs for the PS-InSAR analysis and not 38 pairs (i.e., lines 212 through 213).

Point 10: In line 211, kindly replace 'Master images' with 'Master image'. Other than that, the master image should be approximately at the barycenter of the dataset; what other factors must be considered before accepting the software-recommended master image?

Point 11: SBAS-InSAR applies a multi-looking step to improve coherence in exchange for coarser spatial resolution. The reviewer is curious about the multi-looking parameters (i.e., values in range and azimuth) used in the study.

Point 12: In line 245, where did the 272 interferometric pairs come from?

Point 13: In line 260, how did the authors distinguish fast-subsiding regions? The reviewer suggests that in the early part of the paper, the authors must have set the criteria for fast- and slow-subsiding regions using some citations.

Point 14: The authors compared the annual mean LOS velocities of selected observation points corresponding to the exact geographical coordinates (i.e., line 274). The reviewer is curious if, in one SDFP, there is also one PS. This comment concerns Point 11.

Point 15: How is Figure 9 different from Figure 6?

Point 16: Why the authors only showed the displacement time series for monitoring point C? What about those for points A and B? Also, is the displacement still measured along LOS or in the vertical direction?

Point 17: The authors claim that PSs are not recognized when these PSs exceed a certain velocity. The reviewer is curious if the authors have considered the velocity model used for the PS-InSAR analysis for the loss of PSs.

Point 18: The reviewer wants to clarify if the data fusion discussed and the result presented (i.e., Figure 16) is merely overlying one result obtained from one technique from the result of another. Or, is there a fusion algorithm implemented to enhance the detection and monitoring of fast-subsiding areas?

Point 19: The reviewer suggests that the authors discuss the limitations of the ISODATA algorithm.

Reviewer 3 Report

Dear Authors,

the study presented in this paper is very interesting but the structure of the paper needs to be modified. The method is constantly associated with the results, which are then not adequately discussed. The discussions section is also lacking. The final result is that the paper is very unfocused and disorganized.

I suggest you rewrite the methodology section in detail and separate Methods form Results. You should describe each action in a different section (following the pattern described in paragraph 2.2), then follow the same pattern to describe the results.

My opinion is to reconsider after major revisions.

Atteched you will find the pdf with my suggestions.

Your faithfully.

The reviewer

Comments for author File: Comments.pdf