Round 1

Reviewer 1 Report

The manuscript is generally written well. However, it is difficult to follow the manuscript due to the presentation style. I would suggest to rewite the manuscriot specially the methodology part and present a flowchart so that it is easy to follow that paper. Further, At one place it is given that "The characteristic bands that were selected during modeling were extracted 215
from the Landsat8 OLI image at each sampling point. Since both Landsat5 TM and Landsat8 OLI images needed to be used, it was necessary to select the common bands of the
two images for modeling. Therefore, only the characteristic bands (Band2-Band7) of Landsat8 OLI remote sensing images and their mathematical transformations were considered for modeling." Here authors say that only band 2 and 7 were used however at the later stage all the bands were used. 2ndly No background on the basis of selection of the particular bands were given. I think addition of these will be batter for the presentation of methodology and results. Further, The authors need to provide justification of using the optical data when we have models developed with microwave data also which could provide the opportunity to predict SOC even in the cloudy months. Some examples are "Utilisation of spaceborne C-band dual pol Sentinel-1 SAR data for simplified regression-based soil organic carbon estimation in Rupnagar, Punjab, India" "Synergetic use of multi-temporal Sentinel-1, Sentinel-2, NDVI, and topographic factors for estimating soil organic carbon" and "Prediction of Soil Organic Carbon under Different Land Use Types Using Sentinel-1/-2 Data in a Small Watershed" these work could also be cited in the manuscript.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

The paper presents an abstract with adequate information. The introduction part provides the aim of the study with recent and relevant references. The methodology part gives the details of the application. The results are given with statistical analysis and supported with figures. The validation of the estimations is provided for the year 2020. The discussion section discusses the results and highlights the importance of monitoring the environment. However, I have some suggestions and questions for the authors to clarify some points in the paper.

1.       The title doesn't seem very appropriate because the temporal SOC analysis is not clear. The details on SOC values collection were not provided.

2.       It is mentioned that the SOC values collected in 2020 and the Landsat5 TM and Landsat8 OLI remote sensing images were downloaded. How and why Landsat-5 was downloaded. It was not operational in 2020.

3.       Figure 1 shows the distribution of sapling points, however, some of them are out of the border. Please also put a land use cover map with sampling points.

4.       Lines 163-166: what are the accuracies of the land use map created for the years 1990, 1995, 2000, 2005, 2010, 2015, and 2020? As they are an input for the analysis, they should be reliable.

5.       Line 308 should be revised.

6.       Figure 3 shows the SCO content for a different year. How they are calculated? How many samples were used for each year? It should be clarified in the manuscript.

 

7.       Put the mining intensity level borders (given in figure1) on Figures 4 and 5. It is difficult to follow how SOC values are distributed in space with different mining intensities.

Author Response

Please check the attached file.

Author Response File: Author Response.pdf

Reviewer 3 Report

Dear Authors,

The paper presents a good topic and potentially powerful approach to evaluate and to assess soil organic carbon (SOC) based on Remote sensing data.Here some minor corrections and some clarifications are necessary before the publication.

- Line 158, Please define NDVI index the first time it is mentioned in your manuscript.

-  Need to clarifications or justify the use of Kriging method interpolation in your case

-   How you justify the selections of Landsat 5 TM and Landsat 8 OLI images in your study.

-        - The author should improve the conclusion of their study.

-       -  Rewrite paragraph from line 547 to 552.

-        - The quality of the language needs to improve.

Good luck.

Author Response

Please check the attached file.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The paper has improved and can be accepted.

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

The manuscript is very long hence  more paragraph heading are required because of the number of variables which are being considered..From line 411-414 the authors state that soil type should be used as auxiliary data for remote sensing. I would have considered that land use would be determined by the capability and suitability of the soil.

Reviewer 2 Report

I ask myself why was this work done? the results are entirely predictable without any detailed analyses of the RS data; and have been already reported in many other studies. Additionally, coal mining areas make up a miniscule, miniscule fraction of the land surface. So even a proper study has no implications for climate change, global carbon sequestration, or any of the other huge questions the authors present in the introduction.

I find a fatal flaw in your methods:

Surface sampling of 0-20 cm is questionable. Landsat “sees” only the top few microns of the surface. The correct procedure is to sample, at most, the top cm of soil. Anything deeper can have no relationship to what the RS data are measuring, and are of invalid scientific value.

Reviewer 3 Report

The manuscript with the title "Spatiotemporal patterns of soil organic carbon content in China's Shendong coal mining area during 1990-2020." presents a study that uses predictive models of SOC were developed based on field sampling and Landsat images for different land-use types (grassland, forest, farmland, and unutilized land) for Shendong mining area, the largest coal mining area in China. The paper considers a worthy topic; I believe the structure is good and has merits for being published. However, I have a major concern: I am not sure if the manuscript fits the scope of the Remote Sensing journal. I believe the major components of the manuscripts are related to GIS and not to any scope cited in the journals' scope list. I recommend that the authors revise the manuscript and resubmit if the editor agrees.

 

I have several revisions, but it does not make sense to continue the revision until the major concern is solved.

Reviewer 4 Report

The matter of the manuscript ‘Spatiotemporal patterns of soil organic carbon content in Shendong coal mining area during 1990-2020’ is noteworthy and fits into the scope of the Remote Sensing journal. The presented study is appropriate and thought-provoking, which, in general, deserves publication. Still, the current version of the manuscript requires revisions and additions. I would like to point out the issues I am concerned about.

 

Key questions

L. 143. “75 points in farmland, 54 points in forest land, 119 points in grassland, and 52 points in unutilized land” – what does “unutilized” mean? Is it a barren land, devoid of any plants?

L. 182. “The high-intensity mining area was characterized by relatively continuous working faces, large coal mining height (1.3-4.5 m), and high coal output per unit area” – I do have doubts about the suitability of such criteria for the study of the soil cover. Under the open-cut mining, the upper soil horizon will be stripped away in any case, regardless of the thickness of the coal seam. Furthermore, low or high coal output do not affect the environment in very different ways, it is more about the economic efficiency. Please comment the “coal mining intensity”. Maybe, it is about the mechanized mining as opposed to artisanal mining?

Table 1. – Can we differentiate between carbon formed from organic decomposition and from coal dust? This is of crucial importance for the research of such kind. The authors conclude that “the most influential factor on the SOC content was land use, followed by NDVI, precipitation, temperature, elevation, and mining intensity.” (L. 550). As we see, mining intensity is the last mentioned factor, but is it so indeed? Air pollution and subsequent dust deposition on the soil lead to the changes in carbon geochemistry, but is it considered through the prism of wind direction and intensity, atmospheric inversions, etc.? These parameters may affect the ultimate carbon levels a lot.

 

Minor remarks

Abstract. “Spatially, SOC content increased from the southeast to the northwest of the study area and reached the lowest in the southeast.” – no sense, better tell us about the functional role of these sectors or their soil properties (particle size distribution, moisture level, degree of disturbance, etc.)

L. 55. “At present, there are relatively few studies on SOC estimation in coal mining areas.” – no citations (see for example this paper: https://papers.acg.uwa.edu.au/p/2152_121_Baumgartl/)

L. 142. “a total of 300 field sampling points were collected” – Samples were collected, not sampling points.

 

I honestly hope you will find my suggestions supportive and wish you good luck with the paper.

Kind regards,

Reviewer