Multitemporal Analysis of Land Cover Changes in Areas with Contrasted Forest Management and Conservation Policies in Northern Mexico

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This article is devoted to researches, evaluates and compares vegetation cover in two forested areas in northern Mexico with different management statuses: one with sustainable forest exploitation and the other under protection as a Flora and Fauna Protection Area. The authors analyzed changes in the area and species composition of vegetation in two sites for the period from 1995 to 2022 using satellite imagery, supervised and unsupervised classification methods.

The reviewer has the following questions, suggestions and comments on the article:

1) Why was the assessment of changes in vegetation cover made specifically since 1995? Is this due to the availability of satellite images or other factors?

 2) Why is the hypothesis of an increase in vegetation cover associated specifically with the beginning of 1995? What factors is this associated with? The authors do not indicate this in the article.

3) There is a technical error in lines 122-123 - the authors write about 5 time periods, although there are 4 in total.

4) The authors in the article assess the percentage change in the area and species composition of vegetation cover. However, the only reason given for the dynamics of vegetation cover is human activity (sustainable management, reduced grazing, logging, afforestation, etc.) and for some reason climate factors are not taken into account at all – changes in air temperature, increased precipitation, etc., which have a strong impact on the productivity and species diversity of vegetation cover. The article would be much improved if the authors supplemented it with an analysis of climate data for the period under review.

5) The caption of Figure 4 does not contain the designations A, B, C, D.

 In my opinion, the article needs some revision.

Author Response

Dear Editor, I have attached comments regarding the observations from Reviewer 1. Best regards.

 

This article is dedicated to investigating, evaluating, and comparing vegetation cover in two forest areas in northern Mexico with different management statuses: one with sustainable forest management and the other under protection as a Flora and Fauna Protection Area. The authors analyzed changes in surface area and species composition of vegetation at two sites for the period from 1995 to 2022 using satellite images, supervised and unsupervised classification methods.

The reviewer has the following questions, suggestions, and comments about the article:

Why was the evaluation of changes in vegetation cover specifically conducted from 1995? Is this due to the availability of satellite images or other factors?

Due to the availability of high-resolution satellite images from that date onward.

Why is the hypothesis of an increase in vegetation cover specifically associated with the early 1995s? To what factors is this related? The authors do not indicate this in the article.

To calculate changes (increase or loss) in vegetation cover and land use, a cross-tabulation was generated for five different time periods: 1995-2008, 2008-2014, 2014-2021, and 1995-2022. The year 1995 was chosen as the starting point due to the availability of comparable high-quality satellite data from that year, as well as the initial impact of the General Law of Ecological Balance and Environmental Protection, which established an important framework for environmental conservation in Mexico. Net change, rate of change, and relative percentage change were calculated for each type of vegetation cover or land use over time.

There is a technical error in lines 122-123: the authors write about 5 time periods, although there are 4 in total.

Indeed, there are 4 periods being compared; the wording should be adjusted.

The authors of the article evaluate the percentage change in the area and species composition of vegetation cover. However, the only reason given for the dynamics of vegetation cover is human activity (sustainable management, reduced grazing, logging, afforestation, etc.), and for some reason, climatic factors are not considered at all: changes in air temperature, increased precipitation, etc., which have a strong impact on the productivity and species diversity of vegetation cover. The article would be greatly improved if the authors complemented it with an analysis of climate data for the period under review.

In the land use change analysis conducted, environmental factors were not considered because we do not have meteorological information that would allow us to conduct a comparative analysis of the different periods.

The title of Figure 4 does not contain the designations A, B, C, D.

The periods of the evaluations will be included: 1995 (A), 2008 (B), 2014 (C), and 2022 (D).

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The study deals with a potentially important topic of effectiveness of two contrasting protection systems of forests in Mexico. Results suggest that there is a major problem in a protected area. This message is potentially important for policymakers assuming this case study is not the only case of this kind of a problem. While I feel this study should be published, I have significant concerns about the methods used to analyze the data. As such, it should lead to misinterpretation or even incorrectness of the results.

 

Major comments:

1. I miss detailed descriptions of protection and management methods in both study areas. This should be closely related to the interpretation of the results - why at one (managed) area there is significant increase in forest cover while in the other (protected) there is a decrease? Is it due to the unfavorable conditions caused by climate change or is it because of the insufficient protection and illegal logging?

2. The methods section is very brief, thus it is hard to judge if methods are appropriate. I miss better descriptions of methods used for image preprocessing and processing. Basically, all the boxes in the scheme (Fig. 2) should be described in the methods.

3. Why NDVI was used? This index is well known for quick saturation, thus it might have distorted the result. Instead, e.g. NDRE or EVI could be used. Did you compare more indices? If not, I would like to see the performance of at least one other index. Does the result change significantly?

4. How did you manage different space resolutions of imagery over time? Having bigger pixels at the beginning might cause overestimation of the greenery coverage. Not necessarily, but you should test it. For example, you could aggregate 2022 data and compare with the original data.

5. Some graphical representation of LULC changes would be handy for following the full story. For this purpose, the Sankey diagram would be effective. What categories were reduced at most in Ejido El Largo y Anexos? In other words, are these changes caused by reforestation of grasslands or other unforested areas or is it just a change in type of forest? I see it could be read from the bar plots and table, but it would be worth saying explicitly in the text. The same for the other site.

6. Table 1: You classify only forested areas and grasslands, summing up to 100 %. Is it that there are no other LULCs in the area or you neglect (don't analyze) them? E.g. bare soil, rocks, crop fields, buildings, etc. In the methods you described the classification category of "areas devoid of vegetation", here it is missing. From the text it seems that in the table are shown values of changes (but not marked if gain or loss), however from the table caption it seems that the values are the total area covered by the type of ecosystem (in that case total sums are not matching).

7. In the discussion section, interpretation of results should be more discussed, i.e. the causes of trends in each of the study areas

 

Minor comments:

• Abstract: please avoid mentioning specific software and detailed methods, also abbreviations should not be used. This is supposed to be a general description of a study

• Please place the URL links in the reference section, giving in the text only a cross-reference.

• In the scheme (Fig. 2) there is mentioned that you did not use the unsupervised method of classification, however in abstract you claim you did.

• I would like to see the performance of your classification on the validation data set. Please provide at least a brief summary.

• L154, L281-7: Kappa index should be described in the methods.

• L192-211: belongs to discussion. + some more sections also, please restructure the text.

• Fig. 4: what is shown in A, B, C, D, respectively? Please, describe in caption.

• Fig. 6, 7: showing deforestation is a bit confusing - negative values mean gain of forested area and positive values mean loss. Showing reforestation instead might be more intuitive.

• Discussion: I don't see the point in detailed description of the results of each study, either show them in a summary table or make them brief.

• Graphics are very poor quality: colors of bar plots are too bright, bars overlapping the zero line; in maps on the other hand colors are not very well distinguishable.

Comments on the Quality of English Language

Level of English is good, however there are some typos in the text.

Author Response

Dear Editor, I have attached comments regarding the observations from Reviewer 2. Best regards.

 

The study addresses a potentially important topic: the effectiveness of two contrasting forest protection systems in Mexico. The results suggest that there is a significant problem in a protected area. This message is potentially important for policymakers, assuming that this case study is not the only instance of such an issue. While I believe this study should be published, I have significant concerns about the methods used to analyze the data. These concerns could lead to misinterpretation or even incorrect results.

Main comments:

I miss detailed descriptions of the protection and management methods in both study areas. This should be closely related to the interpretation of the results: why is there a significant increase in forest cover in one area (managed) while there is a decrease in the other (protected)? Is it due to unfavorable conditions caused by climate change, or is it due to insufficient protection and illegal logging?

The following descriptions of both areas were added:

In the Natural Protected Area (ANP), a management program is implemented that includes various conservation subprograms. These subprograms encompass a wide range of interrelated activities focusing on conservation, protection, restoration, management, knowledge, and promotion of environmental culture. Each component of the management program complements and reinforces the others, establishing a comprehensive foundation for environmental policy in the ANP (CONANP, 2014).

On the other hand, the forest management of the Ejido El Largo y Anexos is based on a detailed classification of the surface area according to the types of forests present. Two main types of forest stands are identified, each managed with different silvicultural systems. The Regular Forest is managed using the Silvicultural Development Method, with a ten-year cutting cycle covering the period from 2018 to 2027. In contrast, the Irregular Forest is managed using the Control Method, with a fifteen-year cutting cycle established from 2018 to 2032. These differentiated management strategies allow for sustainable exploitation of forest resources, adapting to the specific characteristics of each type of forest (Ejido El Largo y Anexos, 2018).

The methods section is very brief, making it difficult to judge whether the methods are appropriate. I miss better descriptions of the methods used for image preprocessing and processing. Essentially, all the boxes in the diagram (Fig. 2) should be described in the methods.

Image Preprocessing: To prepare the satellite images prior to their processing and use in the analysis, a geometric correction was performed by taking identifiable control points in each of the images to be processed. These points were systematically distributed in areas with a high degree of confusion due to image reflectance, exposure, noise, and cloud cover.

Atmospheric correction for the images from each time period was done by cropping and subjecting the image to the K-Means unsupervised classification algorithm, which groups cell values into classes using the multivariate data clustering method. Subsequently, the files were converted from raster to vector format for supervised classification.

Why was NDVI used? This index is known for its rapid saturation, which could have distorted the results. Instead, indices such as NDRE or EVI could be used. Did you compare other indices? If not, I would like to see the performance of at least one other index. Do the results change significantly?

The image classification yielded average Kappa index values of 0.79, indicating a substantial level of accuracy in the process.

How did you handle the different spatial resolutions of the images over time? Larger pixels at the beginning could cause an overestimation of vegetation cover. Not necessarily, but you should test it. For example, you could add data from 2022 and compare it with the original data.

For processing the satellite images of different resolutions, radiometric correction and radiometric normalization were performed for each period.

Any graphical representation of LULC changes would be useful to follow the complete history. For this purpose, a Sankey diagram would be effective. Which categories were reduced the most in Ejido El Largo y Anexos? In other words, are these changes caused by the reforestation of grasslands or other non-forested areas, or is it merely a change in forest type? I see that this can be read in the bar graphs and the table, but it would be worthwhile to state it explicitly in the text. The same applies to the other site.

Table 1: You only classify forested areas and grasslands, summing up to 100%. Are there no other LULC categories in the area, or are you neglecting them (not analyzing them)? For example, bare soil, rocks, croplands, buildings, etc. In the methods you described, the classification category of "areas devoid of vegetation" is missing here. From the text, it seems that the table shows the values of changes (but it does not indicate if there is a gain or loss), however, the table title suggests that the values represent the total area covered by the ecosystem type (in which case, the total sums do not match).

Other uses were segregated, such as human settlements, roads, and power transmission lines, with the aim of analyzing only the change in forest cover.

In the discussion section, a more detailed interpretation of the results should be provided, specifically regarding the causes of the trends observed in each study area.

The observation has been addressed.

Minor Comments:

Abstract: Avoid mentioning specific software and detailed methods; abbreviations should also be avoided. This is supposed to be a general overview of the study.

The changes have been made.

Place URL links in the references section, providing only a cross-reference in the text.

Changes Made: The changes have been made.

In the diagram (Fig. 2), it is mentioned that the unsupervised classification method was not used, but the abstract states that it was used.

Correction Made: The abstract has been corrected.

I would like to see the performance of your classification on the validation dataset. Provide at least a brief summary.

Observation Addressed: The observation has been addressed.

✅ L154, L281-7: The Kappa index should be described in the methods.

For the calculation of the concordance and accuracy of the classification results of the high-resolution satellite images, the r.kappa module in GRASS 7.6.0 was used, which determines the Kappa index, by means of the following equation K= (Po-Pe)/(1-Pe), Where: Po = Observed agreement, Pe = Expected agreement by chance, and 1 – Pe = Maximum potential agreement not corresponding to chance. (Quezada et al. 2022):

Quezada AS, Sevilla-Tapia JD, Avilés-Sacoto EC. 2022. Estimation of the deforestation rate in Pastaza and Orellana- Ecuador through the multitemporal analysis of satellite images during the period 2000-2020. Journal of Research in Agronomic and Veterinary Sciences 6: 282-299.

⏳ L192-211: belongs to the discussion. + some more sections as well, please restructure the text.

Some adjustments are made.

⏳ Fig. 4: What is shown in A, B, C, D, respectively? Please describe it in the title.

Figure 4. Evolution of vegetation cover in Ejido El Largo y Anexos and the Tutuaca Protected Natural Area (ANP) for the years 1995 (A), 2008 (B), 2014 (C), and 2022 (D).

⏳ Fig. 6, 7: Showing deforestation is a bit confusing: negative values mean forest area gain, and positive values mean loss. Showing reforestation instead might be more intuitive.

When deforestation values are negative, they indicate a trend in the recovery of forest cover, therefore, a gain in area in the different ecosystems.

⏳ Discussion: I don't see the point of a detailed description of the results of each study, or showing them in a summary table, or making them brief.

Some adjustments are made.

⏳The charts are of very poor quality: the colors of the bar charts are too bright, the bars overlap the zero line; On maps, on the other hand, colors are not very well distinguished.

The map change was made.

Comments on English Language Quality

⏳The level of English is good, however, there are some typos in the text.

The adjustment was made.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This study focuses on land use change and forest management, which has great theoretical and practical value. The suggestion is as follows.

(1) In the Introduction, it is highly commendable that the background and research significance are very solid. However, relevant research is needed, as this section currently focuses more on describing the significance of the study. Firstly, regarding the topic of forest management, it is necessary to add research results from different regions around the world. Secondly, is there any comparison of research methods involved? If so, relevant content can also be added.

(2) The lines 67-71 in the Introduction do not explicitly point out the shortcomings of existing research, simply because the lack of such research in this study area makes it difficult to demonstrate the necessity of this study.

(3) The lines 72-79 in the Introduction do not reflect the contradiction between land use change and forest management in the selected study area, and therefore do not indicate the research perspective.

(4) Lines 82-92, this study focuses on land use change and forest management, but there is no information about these two aspects in the introduction of the study area.

(5) In Figure 1, the text is too small to read clearly.

(6) Lines 96-197, simply telling the reader the flowchart is not enough, at least explain the work content or research steps of this study.

(7) In Figure 3, there are color differences in satellite images from different periods. Do we need to further process this image. As shown in Figure 4, very good. In addition, the text in the picture needs to be clearer, at least the important content.

(8) The result must be divided into sections, otherwise there will be no organization.

(9) The discussion was rich in content, not only discussing the results of this study, but also making comparisons. Suggest considering divided into sections. In addition, it is suggested to add shortcomings and prospects.

(10) The title of the paper mentions Conservation Policies, although Conservation Policies are mentioned multiple times in the results and discussion. I would prefer to see a dedicated section on Conservation Policies presented in the results or discussions.

Author Response

Dear Editor, I have attached comments regarding the observations from Reviewer 3. Best regards.

 

This study focuses on land-use change and forest management, which has great theoretical and practical value. The suggestion is as follows:

(1) In the introduction, it is very laudable that the background and importance of the research are very solid. However, relevant research is needed, as this section is currently more focused on describing the importance of the study. First, with regard to the topic of forest management, there is a need to aggregate research results from different regions of the world. Second, is there any comparison of the research methods involved? If so, relevant content can also be added.

Added information in introduction.

(2) Lines 67 to 71 of the Introduction do not explicitly point out the shortcomings of existing research, simply because the lack of such research in this area of study makes it difficult to demonstrate the need for this study.

Se agregó el siguiente texto para aclarar la importancia de la investigación: This information will be of importance to officials and decision makers in the management and conservation of forests in Mexico, as it will provide a basis for determining the effectiveness of forests managed and designated for conservation.

(3) Lines 72-79 of the Introduction do not reflect the contradiction between land-use change and forest management in the selected study area and therefore do not indicate the perspective of the research.

It was indeed not clear. The following information was added: In this study we analyzed two contrasting areas according to their management. The first has been managed in natural forests since the beginning of the 20th century [25] and the second is a Flora and Fauna Protection Area "Tutuaca", designated in 1937, where no logging or land use change is allowed [26].

(4) Lines 82-92, this study focuses on land-use change and forest management, but there is no information on these two aspects in the introduction to the study area.

Added detailed information on materials and methods.

(5) In Figure 1, the text is too small to read clearly.

Font size increased.

(6) Lines 96-197, simply telling the reader the flowchart is not enough, at least explain the content of the paper or the research steps of this study.

Adjustments are made.

(7) In Figure 3, there are color differences in satellite images from different periods. Do we need to process this image further? As shown in Figure 4, very good. Also, the text in the image should be clearer, at least the important content.

This is due to the quality of the satellite images found for each period, unfortunately these images do not have homogeneity.

(8) The result must be divided into sections, otherwise there will be no organization.

It is divided into four sections.

(9) The discussion was rich in content, not only discussing the results of this study, but also making comparisons. He suggests considering breaking it down into sections. In addition, it is suggested to add deficiencies and perspectives.

The "Policies and Perspectives" section was added at the end of the discussion.

(10) The title of the article mentions conservation policies, although these policies are mentioned several times in the results and in the debate. I would prefer to see a section dedicated to conservation policies included in the results or discussions.

The "Policies and Perspectives" section was added at the end of the discussion.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

The sustainable forest development is important since it allows to keep the balance of sustainable development and environment conservation. Forestry engineering is an important constituent of biodiversity conservation.

The techniques of tracking and monitoring the forest cover change with time allow to forecast and make managerial decisions on forest conservation and regeneration.

The implementation of multitemporal analysis for the evaluation of forest cover change on the territory under examination is worth mentioning.

The study is a complete research, theme of the study is relevant to the Journal research line. Literature review complies with the research.

The study could further benefit, if the authors had presented their proposals on the application of their approach to other regions and countries.

Author Response

Dear Editor, I have attached comments regarding the observations from Reviewer 1. Best regards.

 

Sustainable forestry development is important because it allows the balance between sustainable development and environmental conservation to be maintained. Forest engineering is an important component of biodiversity conservation.

Techniques for monitoring and controlling forest cover change over time make it possible to predict and make management decisions on forest conservation and regeneration.

The application of multitemporal analysis for the evaluation of forest cover change in the territory under study is noteworthy.

The study is a complete investigation, the subject of the study is relevant to the Journal's line of research. The literature review is in line with the research.

⏳The study could benefit even more if the authors had submitted their proposals on the application of their approach to other regions and countries.

The approach we present is on the paradigm of the designation of protected natural areas, which does not necessarily guarantee the conservation of forest ecosystems and responsible forest use affects the recovery of forest cover, with the effect of stimulating natural regeneration and reforestation in degraded areas.

Author Response File: Author Response.pdf

Reviewer 5 Report

Comments and Suggestions for Authors

This paper evaluates and contrasts the changes in vegetation cover over three decades in two management statuses in northern Mexico. The satellite images from five periods were analyzed based on the QGIS and supervised classification method. This manuscript provides a comprehensive analysis of vegetative cover dynamics and highlights the effect of management and conservation policies. However, the authors should consider the following specific revisions before publication.

[1]    Some specific information and results are not reflected in the Abstract part, which makes it difficult to clearly understand and recognize the significance of this study through the existing information.

[2]    L20-21: It is necessary to introduce the specific locations and differences of these two management statuses, otherwise it will be difficult to understand the results later.

[3]    L23: Was the unsupervised classification used in this study?

[4]    L24: 2014-2021?

[5]    L26-29: Quantitative results need to be provided.

[6]    L48 and 54: The two management statuses of establishing conservation sites and sustainable forest management require detailed explanation. What specific means are used?

[7]    Abstract and Introduction parts: Some geographical relationships are not introduced, making them difficult to understand.

[8]    L86: “ejido”?

[9]    The font in the Figure 1 is unclear.

[10]    L118-119: The historical land use data and field surveys need to be introduced in detail.

[11]    Materials and Methods: The evaluate method for classification accuracy need to be introduced.

[12]    All figures need to be normalized.

[13]    Figure 4: What do A, B, C, and D stand for?

[14]    L228: The p value of statistical analysis should be given for significant changes.

[15]    L230-231: there was a notable increase in oak forest area, with a relative change rate of -45.96%... Please check it in conjunction with Eq. (3) and Figure 5. Why is it negative?

[16]    L228-243: Please check the data for relative change.

[17]    L272: The p value of statistical analysis should be given for significant increase.

[18]    I suspect that the values of all the relative changes in the paper are inconsistent with Eq. 3, please check them.

[19]    There are no secondary headings in the two parts of Results and Discussion, which makes the logic unclear.

[20]    The Discussion section should explicitly respond to the hypotheses proposed by this study.

[21]    Conclusion part lacks data support.

Comments on the Quality of English Language

English Language is ok.

Author Response

Dear Editor, I have attached comments regarding the observations from Reviewer 5. Best regards.

 

This article evaluates and contrasts changes in vegetation cover over three decades in two management states in northern Mexico. Satellite imagery from five periods was analyzed based on the QGIS and the supervised classification method. This manuscript provides a comprehensive analysis of vegetation cover dynamics and highlights the effect of management and conservation policies. However, authors should consider the following specific reviews before publication.

[1]     Some specific data and results are not reflected in the Summary portion, making it difficult to clearly understand and recognize the importance of this study through existing information.

Added information.

[2]     L20-21: It is necessary to introduce the specific locations and differences of these two management states, otherwise it will be difficult to understand the results later.

Added information.

[3]     L23: Was unsupervised classification used in this study?

An unsupervised classification was performed with the multivariate data cluster analysis method and then the conversion of the files from raster to vector format is carried out, for supervised classification.

[4]     L24: 2014-2021?

Fixed in year.

[5]     L26-29: Quantitative results should be provided. (In the summary)

Added information.

[6]     L48 and 54: The two management states, the establishment of conservation sites and sustainable forest management, require detailed explanation. What specific means are used?

The observation was addressed.

[7]     Summary and Introduction Parts: Some geographical relationships are not introduced, making them difficult to understand.

The observation was addressed.

[8]     L86: ¿“ejido”?

Replaced by area.

[9]     source in Figure 1 is unclear.

The observation was addressed.

[10]     L118-119: Historical land-use data and field studies need to be entered in detail.

The observation was addressed. The observation was addressed. Are the second and third paragraph of materials and methods.

[11]     Materials and methods: It is necessary to introduce the method of evaluation of the accuracy of the classification.

Image pre-processing. To prepare the satellite images prior to their processing and use in the analysis, a geometric correction was made by taking identifiable control points in each of the images to be worked on, which consisted of sites systematically distributed in areas with a high degree of confusion due to the reflectance of the images.  exposure, noise and cloudiness.

The atmospheric correction to the images of each time period was performed by cropping and subjecting the image to the unsupervised classification algorithm K-Means, which groups cell values into classes with the multivariate data cluster analysis method; then the conversion of the files from raster to vector format is carried out, for supervised classification

[12]     All figures must be normalized.

The change was made.

[13]     Figure 4: What do A, B, C, and D mean?

Figure 4. Evolution of vegetation cover in Ejido El Largo y Anexos and the Tutuaca Protected Natural Area (ANP) for the years 1995 (A), 2008 (B), 2014 (C), and 2022 (D).

[14]     L228: The p-value of the statistical analysis should be provided for significant changes.

Se integra.

[15]     L230-231: There was a notable increase in the area of oak forest, with a relative rate of change of -45.96%... Check this together with equation (3) and figure 5. Why is it negative?

The result is correct, it refers to the reforestation rate, in previous lines it is mentioned.

[16]     L228-243: Check the data for relative changes.

If there are relative changes.

[17]     L272: The p-value of the statistical analysis should be provided for a significant increase.

P value is integrated.

[18]     I suspect that the values of all relative changes in the article are inconsistent with equation 3, please check them.

The results are correct according to the calculation made.

[19]     are no subtitles in the two parts of Results and Discussion, which makes the logic unclear.

It is divided into four sections.

[20]     The Discussion section must explicitly respond to the hypotheses proposed by this study.

The hypothesis is explicitly answered in the discussion, it is mentioned that in the conservation area there is a loss (the hypothesis is rejected), while in the management area there is an increase (the hypothesis is accepted).

[21]     The concluding part lacks data support.

We consider that it would be repetitive to mention the outcome data again in the conclusions section.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Overall, the manuscript was improved, but not as much as I supposed. There are still many issues, some of them major, left to address.

 

Some of my comments were not addressed:

1) I previously asked for a better description of methods. I.e. to explain all the steps denoted in the diagram and provide exact methods and software that were used. Otherwise the work is not replicable and thus cannot be checked for correctness. It is not sufficient to answer in the comments to the review, my point is that all readers should be able to completely understand the workflow, not just the reviewer.

2) Kappa index should be explained or at least mentioned and cited in the methods section. You addressed the method in the comments but not the text itself. Please provide the method description. Moreover, you need to describe which baseline data you used for comparison. The only thing you mention (in results!) is that "Maps representing land cover..., were generated for the years 1995, 2008, 2014, and 2022." That doesn't explain anything. If you generated some maps of classification and compared it to other maps of classification you generated as well, it is not how the kappa index is used. You should either compare your results to ground truth, i.e. field observations, or some other INDEPENDENT classification that is considered as correct. I don't see in your description any of it.

 

I am still not very satisfied with the explanation of NDVI use. As I mentioned before, it is well known for rapid saturation and due to that it can lead to dissort of results. Author's explanation of validity supported by the kappa index cannot be accepted as the kappa index itself is not generally considered as reliable (as authors themselves admit in the discussion), and also due to my concerns about the methodology mentioned above. To conclude this point, I insist on either using some other vegetation index for comparison or detailed convincing proof of correctness of NDVI use.

 

L195: I still miss the information which particular LULC(s) decreased the area

Table 1: Still does not contain other LULCs so the total area (sum) would match among years. You claim in the text that in Ejido El Largo y Anexos the total coverage of the forest ecosystem was increasing, while in the table it seems that it is decreasing (from 105,101 ha in 1995 to 72,914 ha in 2022). In Protected Natural Area Tutuaca vice versa. Is the table showing losses (I suppose so)? In that case the caption is wrong.

 

Fig.5: Again, the caption of the figure is probably wrong. Showing the "relative change" of -45 % means that the area was actually reduced (from 100 to 55). In the text you claim the opposite, i.e. regain in Ejido El Largo y Anexos and reduction in Tutuaca Protected Natural Area. You probably mean relative change RATE here.

 

Again, in the Discussion: I don't see the point in detailed description of the results of each study, either show them in a summary table or make them brief. You don't need to show all the numbers, just briefly compare the trend if it is the same or different and discuss why. In such a study as yours it is absolutely obvious that all the case studies will show different results, because it depends on local conditions, people's mentality, etc.

 

Minor comments/typos:

 

Once you introduce the abbreviation, do not use the full name further (Protected Natural Area - PNA), also it is not unified throughout the text which feels a bit confusing. Figure a table captions still should contain the full name.

 

I would like to stress out here once again that the paper is a bit complicated to read. Please, try to help the reader to understand and follow your story, I already suggested some changes, unfortunately those were not incorporated. So once again:

 

- I'd like to see the Sankey diagram, as I denoted in my first review. It would very much help the readability of the study.

- Fig.4: It is still very hard to distinguish between some shades of colors, which makes the map very hard to read. I don't see big difference between this and the previous version. Changing yellow to some shade of gray and better distinguishing between Grassland and Pine-Oak forest might help (e.g. make Grassland yellow).

- Please, do something with the graphics, as I asked you in the previous review. Use clear thin lines, pale or no colors (as you follow the order of the ecosystem types it is not necessary to use colors for determination), avoid the thick box borders, as they cause the box itself to be larger than the actual values are.

- Fig. 6, 7: I repeat my comment here. "Showing deforestation is a bit confusing: negative values mean forest area gain, and positive values mean loss. Showing reforestation instead might be more intuitive." Please consider using "reforestation" instead of "deforestation". I understand what the numbers mean, my point is that reading and understanding such graphs is much harder than the one I suggest. You should help the reader to orient in your study as much as you can.

 

- L104: extra "management"

- To "allow for" means to consider someone or something when you are planning something, while to "allow" means to give permission for someone to do something, or to not prevent something from happening. Please check the meaning throughout the text and correct where appropriate.

- L197: "ejido" should be probably with capital E

Comments on the Quality of English Language

some typos left, I denoted in the main review body

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have completed the revision with high efficiency and high quality, and it is recommended for publication.

Author Response

Comments 1: The authors have completed the revision with high efficiency and high quality, and it is recommended for publication.

 

Response 1: We appreciate your review and suggestions, which allowed us to substantially improve the manuscript.

Reviewer 5 Report

Comments and Suggestions for Authors

Authors have responded to my comments and made corrections. I recommend acceptance after making some minor editorial changes.

L103-104: “management, management,”? check it.

L146: “2014-2021”, check it.

Author Response

Comments 1: Authors have responded to my comments and made corrections. I recommend acceptance after making some minor editorial changes.

 

L103-104: “management, management,”? check it.

L146: “2014-2021”, check it.

 

Response 1: We appreciate your review and suggestions, which allowed us to substantially improve the manuscript. We appreciate your review and suggestions, which allowed us to substantially improve the manuscript. We made the indicated modifications.

 

Round 3

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript was improved overall, but there are still some issues that were not addressed well or at all and the authors keep ignoring them. I appreciate that some of my requests were addressed, i.e. the better explanation of methods, and better readability of maps and graphs.

What I also appreciate is including the Sankey diagram, however, this is not the way I meant it would be used. It should show interchanges among the LULC categories in all the time frames. The first column would be the original state of LULC distribution in 1995, the second column LULC distribution in 2008, the third in 2014, and the last in 2022. Stripes would show redistribution of all LULCs among categories, i.e. how much of each forest type turned into a non-forested type and vice versa. I should also show if the change were continuous or in a narrow time window.

 

Some other of my comments were not sufficiently (or at all) addressed:

- You need to mention the kappa index in methods and describe the data set against which your results of classification were tested. This is necessary to determine if the method is appropriate (see the theory paragraph below).

- Table 1: Please double-check the table caption and contents. It does not correspond to the text. If it was the total area, it would be as follows:

- "Among the main ecosystems, those showing the greatest recovery by 2022 were oak forest, which regained 9,470.64 hectares (29%) of its 1995 coverage": Contents in Table 1 show 23,972 ha in 1995 and 14,501 ha in 2022, which means LOSS of 9,470 ha

- "followed by pine-oak forest with a recovery of 8,976.09 hectares": Contents in Table 1 show 13,969 ha in 1995 and 11,230 ha in 2022, which means a LOSS of 2,739 ha (here even the number doesn't match)

- "and the Pine forest, which regained 9,044.57 hectares": Contents in Table 1 show 29,915 ha in 1995 and 20,871 ha in 2022, which means a LOSS of 9044

- I'm not going to write down all the mismatches, once again please double-check. This is not acceptable for publishing.

- Again, in the Discussion: I don't see the point in describing the results of each study in detail, nor in showing them in a summary table or making them brief. It’s unnecessary to show all the

numbers; just briefly compare the trend if it's the same or different and analyze why. In a study like yours, it’s absolutely obvious that all case studies will show different results, because it depends on local conditions, people's mindset, etc.

 

Minor notes:

L154: What are the reference data you use?

There are two Figures 4  ano no Figure 5

The word "data" is plural, thus use "data are" not "data is". Please check throughout the text.

You use the verb "to allow for" instead of "to allow". Please check throughout the text.

 

I include some theory on the kappa index, please prove me wrong if I'm not correct:

 

When comparing different resolutions, you obtain a consistency check, not proof of validity: Comparing kappa indices from classifications on different resolution images can provide insights into the consistency of your algorithm across different data sets. If the kappa value remains relatively high across different resolutions, this might suggest that your algorithm is robust. However, this is not direct proof of the validity of the classification algorithm itself; it’s more a measure of its consistency.

The validity of kappa comparisons depends heavily on the ground truth data. The ground truth should be accurate and relevant to both resolutions. If the ground truth is more aligned with one resolution than the other, this could bias the kappa results.

The most reliable way to prove the validity of your classification algorithm is to validate it on independent datasets. This means applying your algorithm to different satellite images that have not been used in the training process and comparing the results to a reliable ground truth.

Consider using other metrics in conjunction with kappa, such as overall accuracy, F1-score, precision, and recall. These can provide a more comprehensive understanding of your algorithm's performance.

Comments on the Quality of English Language

See my points in the main review text

Author Response

Response to Reviewer 3 Comments

Comments 1: I include some theory on the kappa index, please prove me wrong if I'm not correct:

When comparing different resolutions, you obtain a consistency check, not proof of validity: Comparing kappa indices from classifications on different resolution images can provide insights into the consistency of your algorithm across different data sets. If the kappa value remains relatively high across different resolutions, this might suggest that your algorithm is robust. However, this is not direct proof of the validity of the classification algorithm itself; it’s more a measure of its consistency.

The validity of kappa comparisons depends heavily on the ground truth data. The ground truth should be accurate and relevant to both resolutions. If the ground truth is more aligned with one resolution than the other, this could bias the kappa results.

The most reliable way to prove the validity of your classification algorithm is to validate it on independent datasets. This means applying your algorithm to different satellite images that have not been used in the training process and comparing the results to a reliable ground truth.

Consider using other metrics in conjunction with kappa, such as overall accuracy, F1-score, precision, and recall. These can provide a more comprehensive understanding of your algorithm's performance.

.

Response 1: We appreciate your review and suggestions. Most studies to determine land use change processes use Landsat (30m/pixel) and Sentinel (10m/pixel) satellite images, cataloged as low and medium resolution respectively (EOS, 2020), which, by combining bands, relate the values ​​relative to the color, tone and intensity of radiation, grouping pixels with similar spectral characteristics present in the image, allowing to estimate the quantity, quality and development of vegetation through the Normalized Difference Vegetation Index (NDVI), which requires stages of training, classification and precision analysis and verification of results.

However, this type of images present a series of limitations due to the high percentage of cloud cover in certain periods, invalid data bands, pixel overlap in two consecutive images, generating a margin of erroneous classification between 10 to 30% (Astola et al. 2019, Sandoval-García et al. 2021), while the use of high-resolution satellite images (<5 m/pixel), allow a better classification of the different land uses and vegetation, because they can be manipulated in enhanced wavelet compression (ecw) format, which considerably reduces the file size, while maintaining high graphic quality and a high degree of detail (Pham et al., 2016; Azzari et al., 2017).

Author Response File: Author Response.pdf