Study on Spatiotemporal Characteristic and Mechanism of Forest Loss in Urban Agglomeration in the Middle Reaches of the Yangtze River

Round 1

Reviewer 1 Report

I like the research idea, the research design, and its execution. The authors identified the research gap and an important current ecological and economical problem – deforestation and afforestation due to various reasons, urbanization being the major reason - and undertook to fill it with reviewed paper.

The whole rationale behind the chosen methods, all used data sources, and assumptions were thoroughly explained. The procedure is replicable if someone would like to use it for a different area on which used data exists.

The reviewed study is well-grounded in the existing literature and the provided discussion points to how it is relatable to other works in this field.

One of the small issues is the lack of the description of the structure of the paper in Section 1: Introduction, i.e. stating what each section deals with, would help with quicker navigation through the paper for the interested readers.

Language is adequate and allows for following the authors' argumentation easily.

It was an interesting read, good work!

Author Response

Response to Reviewer 1

 

Dear Reviewer:

 

Thank you very much for your valuable comments on our manuscript entitled “Study on Spatiotemporal Characteristic and Mechanism of Forest Loss in Urban Agglomeration in the Middle Reaches of the Yangtze River”. Those comments are very helpful for revising and improving our paper. According to these comments, we have revised the manuscript in detail. The main modifications are in the manuscript and the responds to comments are as follows (the replies are highlighted in blue).

 

1. One of the small issues is the lack of the description of the structure of the paper in Section 1: Introduction, i.e. stating what each section deals with, would help with quicker navigation through the paper for the interested readers.

 

Thank you very much for your guidance. According to your comment, we have added the contents about the description of the structure of the paper in Section 1: Introduction, as follows:

The structure of the study can be divided into five parts. The first part is the Introduction, which introduces the research background, research object, existing theories, methods, and common data. The second part is Materials and Methods, which establishes the methodology for forest loss analysis in the UAMRYR. The third part is Results, which elaborated the overall forest loss, the spatial distribution of forest loss and its causes, the forest loss in important areas. The fourth part is the Discussion, which summarizes the spatiotemporal characteristic and mechanism of forest loss in the UAMRYR, puts forward several countermeasures to curb forest loss, and presents the limitations of the study. The fifth part is the Conclusion, which presents the highlights of the results.

In order to give readers a clearer understanding of the methodology of this paper, we have added the following contents:

This approach can be divided into five steps. First, the scope of the research area was clar-ified, and the LULC, Landsat, Google Earth, and other datasets were collected. Second, the datasets underwent project correction, geometric correction, and image optimization and were then imported into ArcGIS. For all areas where forest vegetation had been re-moved, Landsat and Google Earth images were compared to determine the causes of for-est change and generate a spatial database reflecting forest and other landcover changes. Third, using the spatial database, a grid system composed of massive grid cells was es-tablished to determine total forest loss and identify the cause for each grid cell. Statisti-cal calculations were carried out on all grid cells, and the complex spatial changes in for-est cover can be reflected. Fourth, the grid cells where forest area changes occurred in each time period were determined. The coordinate systems representing the regional dif-fer-ences and characteristics of forest loss were established using the centrifugal model and were classified into several categories according to their impact degree and scope. Fifth, the forest loss in the coordinate systems was analyzed and compared with the spa-tial dis-tribution of forest loss in the grid system. The spatial characteristics and mecha-nism of forest loss can then be summarized.

 

Once again, thank you very much for your good comments and suggestions which helped us to improve the quality of the manuscript. If you have any other comments on this manuscript, we are very happy to follow your comments for further revision.

 

Kind regards.

Author Response File: Author Response.docx

Reviewer 2 Report

Dear author(s),

The manuscript proposed a new approach to evaluate the spatiotemporal characteristics regarding the forests area in Yangtze River. The manuscript has been well-prepared, although several comments can be made to improve the manuscript quality and to add clarity to the overall manuscript, as follows:

Introduction

1. The authors explain the various methods available to track the forest dynamics using GIS and RS data and technology, and offers the new approach to evaluate the dynamics of forest loss. However, there is no explanation or link that suggests the needs of the new approach, nor explanation of the difference from the new approach as compared to the other available methods.

Methods

1. Spatial differentiation for forest loss were interpreted by using visual interpretation, can you explain what kind of data that you were used to interpret the change from 1990-1995 to 2015-2020?
2. n in the equation 3 refers to the cause of forest loss, the n is limited to 1 to 4. Can you explain why the cause is limited to 4?
3. I don’t understand the main and subordinate coordinate systems within the grid, can this perhaps be illustrated in a figure?
4. What it the reason for choosing 10 as the threshold for excluding the subordinate location? What is the unit of D?
5. As for point 2 and 5, lots of reasoning behind the values grid system was left unexplained. Please add better explanation regarding this, and add an illustration to better depict the methods.

Results

1. Results showed that there were 5 causes for forest loss, while you used 4 as the cause for the forest loss as mentioned in the methods, please elaborate
2. Please add the temporal information (from what year to what year) to each subfigures. In addition, was the 1990 – 1995 interpretation also conducted using the high-resolution data?
3. Figure 4, typo – cauesd for the map legend, in addition, since the loss were relatively scattered and small on that scale. The information on the maps can not be seen clearly. Please consider to add inset map to highlights some areas with major changes.
4. What are the meaning from the terminology of primary, secondary, tertiary and independent coordinate systems? And how is this relate to the analysis
5. Its hard to grasp that many information from fig 7. Which I believe can be better displayed as a table.

 

Author Response

Response to Reviewer 2

 

Dear Reviewer:

 

Thank you very much for your valuable comments on our manuscript entitled “Study on Spatiotemporal Characteristic and Mechanism of Forest Loss in Urban Agglomeration in the Middle Reaches of the Yangtze River”. Those comments have helped us a lot to improve the manuscript. We study your comments very carefully, and revised the manuscript in detail. The main modifications are in the manuscript and the responds to comments are as follows (the replies are highlighted in blue).

 

1. The authors explain the various methods available to track the forest dynamics using GIS and RS data and technology, and offers the new approach to evaluate the dynamics of forest loss. However, there is no explanation or link that suggests the needs of the new approach, nor explanation of the difference from the new approach as compared to the other available methods.

Thank you very much for your comment. We added contents in the 1. Introduction to explain the necessity of establishing new approach, and elaborate the relationship and difference between our methods and existing available methods, as follows:

These datasets and methods have their own advantages. However, if only one is used, it would be difficult to comprehensively and accurately analyze forest loss at the scale of urban agglomeration. LULC data can be used to analyze the spatial change in forests but have difficulty identifying the causes of forest change. Remote sensing data (e.g., AVHRR, MODIS, Landsat, ALOS, SPOT, and ENVISAT) can reflect the causes of macro-level forest change but can not reflect the causes of forest change at the micro-level given their 30 m resolution. Google Earth provides a higher resolution and can reflect trends and causes of forest change at the micro-level, but the dataset has not been vectorized, which makes it difficult to process. LTDR and RFA can accurately analyze spatial trends of forest loss or growth in a certain region but have difficulty reflecting spatial distribution. Existing CA methods can reflect the macro spatial distribution of forest growth or loss but have limited capabilities reflecting micro-level changes and the dynamic factors causing the change. TLS and Thermal Imaging can analyze micro-level changes in forests and its dynamic factors, but their datasets must be obtained by professional equipment, making it difficult to obtain necessary data for huge regions, such as urban agglomerations.

In this study, we developed a new approach to evaluate the spatiotemporal charac-teristics and dynamic mechanism of forest loss in urban agglomerations. This approach can be divided into five steps. First, the scope of the research area was clarified, and the LULC, Landsat, Google Earth, and other datasets were collected. Second, the datasets un-derwent project correction, geometric correction, and image optimization and were then imported into ArcGIS. For all areas where forest vegetation had been re-moved, Landsat and Google Earth images were compared to determine the causes of for-est change and generate a spatial database reflecting forest and other landcover changes. Third, using the spatial database, a grid system composed of massive grid cells was es-tablished to deter-mine total forest loss and identify the cause for each grid cell. Statistical calculations were carried out on all grid cells, and the complex spatial changes in forest cover can be re-flected. Fourth, the grid cells where forest area changes occurred in each time period were determined. The coordinate systems representing the regional differ-ences and character-istics of forest loss were established using the centrifugal model and were classified into several categories according to their impact degree and scope. Fifth, the forest loss in the coordinate systems was analyzed and compared with the spatial dis-tribution of forest loss in the grid system. The spatial characteristics and mechanism of forest loss can then be summarized. This approach adopts time series analysis of the LTDR and the spatial unit division and discrete analysis in the CA and can utilize the advantages of the LULC, Landsat, Google Earth, and other spatial data. The proposed ap-proach is expected to ac-curately analyze spatial trends, characteristics, and mechanisms of forest loss in urban agglomerations and other regions.

 

2. Spatial differentiation for forest loss were interpreted by using visual interpretation, can you explain what kind of data that you were used to interpret the change from 1990-1995 to 2015-2020?

We are very sorry that the method of interpretation is not accurately described in the original manuscript. So we added the contents about the interpretation in the 2.3.2. Spatial differentiation for forest loss, as follows:

The Arcscan and Raster Calculator functions of ArcGIS were used to automatically com-pare the images and evaluate the change in landcover [62]. If a forest polygon is replaced by urban built-up areas, expressways, and railways in a certain period, the cause of forest loss for this polygon is assumed to be construction [63]. If a forest polygon is replaced by grassland, farmland, or bare land, the cause of forest loss may be logging, fire, or pollution. The cause must then be clarified using visual interpreta-tion on high-resolution images, such as Google Earth. For instance, if the high-resolution image corresponding to forest polygon is black or dark brown, or the dark brown area is mixed with grassland, the cause of forest loss is assumed to be fire. If the corresponding high-resolution image is gray-ish-white or grayish-yellow, the cause of forest loss can be determined as pollution. If there is no obvious fire and pollution occurrence in the corre-sponding high-resolution image, or there are regular tree stumps in agricultural land and grassland, the cause of loss can is assumed to be logging [64]. The cause of forest loss for each polygon was determined and inputted into the database to generate the spatial distribution of forest loss and overall landcover change.

 

3. n in the equation 3 refers to the cause of forest loss, the n is limited to 1 to 4. Can you explain why the cause is limited to 4?

We’re very sorry that we didn't explain the meaning of n clearly in the original manuscript. So, we explain its meaning below the equation 3, as follows:

Since there are four causes of forest loss: fire, logging, construction, and pollution, the n in one cell shall not be greater than 4.

 

4. I don’t understand the main and subordinate coordinate systems within the grid, can this perhaps be illustrated in a figure?

According to your comment, we added the figure.7 to illustrate the meaning and relationship of main and subordinate coordinate systems.

Figure 7. Coordinate systems of forest loss.

 

We also added some contents to explain the meaning and relationship of main and subordinate coordinate systems in the 2.3.4. Establishment of forest loss coordinate systems, as follows:

A subordinate coordinate system belonging to a main coordinate system indicates that it is under the influence of the main coordinate system and that the forest loss is likely to be affected by the main coordinate system. The main coordinate systems in dominant levels often have a larger scope and greater influence on the surrounding area and have more subordinate coordinate systems. They are often the most important areas of forest loss.

Due to the unclear expression in the original manuscript, we revised the content about the classes of the coordinate systems in the 3.3. Analysis of forest loss in important areas, as follows:

Using the calculation method of subordination, the coordinate systems in the UAMRYR were evaluated and grouped into classes. Three were categorized as primary coordinate systems within the three metropolitan areas of CZTMA, WMA, and NMA. These areas have the most concentrated and severe forest loss in the entire UAMRYR and significantly impact the surrounding areas. Eighteen were secondary coordinate systems in the cities of Xiangyang, Jingmen, Yichang, Jingzhou, Yueyang, Yiyang Loudi, Heng-yang, Changde Yichun, Pingxiang, Xinyu, Ji'an, Fuzhou, Yingtan, Jiujiang, Jingdezhen, and Shangrao. While their degree and influence range of forest loss were less than that of the primary coordinate system, they had a particular ef-fect on nearby areas. In addition, there were 329 tertiary coordinate systems and 442 qua-ternary coordinate systems, both having far less influence and scope than the primary and secondary coordinate systems and most belonging to the coordinate systems in the first two levels.

 

5. What it the reason for choosing 10 as the threshold for excluding the subordinate location? What is the unit of D?

Thank you very much for your suggestion. We added the sentence about the unit of D below the equation 4:  D is the distance between the origins of the subordinate and main coordinate systems, and its unit is the side length of the grid cell (5km). After consideration, we believe that due to the large influence range of the primary coordinate system such as WMA, the upper limit of D should not be set. Therefore, we deleted sentences related the threshold of D in the context.

 

6. As for point 2 and 5, lots of reasoning behind the values grid system was left unexplained. Please add better explanation regarding this, and add an illustration to better depict the methods.

In order to better depict the methods, we added the Figure 2. Grid system of UAMRYR and the example of grid cell.

Figure 2. Grid system of UAMRYR and the example of grid cell

We also added the explanation for the reasoning of the grid system in the 2.3.3. Construction of grid system, as follows:

In the urban agglomeration, forest loss and landcover change are extremely complex and difficult to quantify or describe directly. A grid system helps standardize complex changes and unify the spatial system for statistical operation. The smaller the area and the more the number of cells in the grid system, the more accurate the calculation results would be, but the number of calculations would also increase. Therefore, the area and number of cells need to be determined according to the scale of the research region.

 

7. Results showed that there were 5 causes for forest loss, while you used 4 as the cause for the forest loss as mentioned in the methods, please elaborate

This is the ambiguity caused by our negligence. Actually, there are 4 causes for forest loss in UAMRYR: fire, logging, construction and pollution. The mining and pollution in the original manuscript is an inaccurate and ambiguous expression. The mining and industry are the main causes of pollution which caused the forest loss. Therefore, mining and pollution should not be expressed in apposition, but should be combined into pollution. So we revised all “mining and pollution” to “pollution” throughout the manuscript. The figure.4 Reason classification of forest loss was revised also.

 

8. Please add the temporal information (from what year to what year) to each subfigures. In addition, was the 1990 – 1995 interpretation also conducted using the high-resolution data?

According to your comment, we added the temporal information (i.e., 1990-2020) to all subfigures in each figure. The 1990 – 1995 interpretation also conducted using the high-resolution data of Google Earth with the resolution of 10-30 m. The resolutions of Google Earth images in 1990-2000 are lower than its images in 2005-2020, but higher than the contemporaneous images of Landsat. We modified the related sentences in 2.2. Data Sources, as follows:

Google Earth dataset was obtained from the Google Earth Pro software (version: 7.3.3). Its image resolution is 10-30 m for 1990-2000 and 0.6-10 m for 2005-2020 is, which can be used as reference for Landsat and LULC data.

 

9. Figure 4, typo – cauesd for the map legend, in addition, since the loss were relatively scattered and small on that scale. The information on the maps can not be seen clearly. Please consider to add inset map to highlights some areas with major changes.

We revised the Figure 4 (Now is the Figure 5) according to your comments. The typo in figure was modified, and three inset maps were added into figure to highlight the areas with major changes, including the CZTMA, WMA, and NMA, as follows:

Figure.5 Spatiotemporal loss of forest in UAMRYR: (a) Forest loss in 6 periods during 1990-2020; (b) Distribution of forest losses caused by various reasons during 1990-2020.

Because of the huge scope of the UAMRYR, the distribution of forest loss in UAMRYR are very dispersed. Despite various attempts, we are still unable to clearly express the forest loss in various periods and caused by various reasons in Figure 5. Therefore, the figure 5 is only used as a figure representing the original data. The specific forest loss caused by various reasons is clearly expressed in Figure 6.

 

10. What are the meaning from the terminology of primary, secondary, tertiary and independent coordinate systems? And how is this relate to the analysis

We’re very sorry that we didn't explain the coordinate system accurately in the original manuscript. Therefore, we revised related content in the 3.3. Analysis of forest loss in important areas, as follows:

Using the calculation method of subordination, the coordinate systems in the UAMRYR were evaluated and grouped into classes. Three were categorized as primary coordinate systems within the three metropolitan areas of CZTMA, WMA, and NMA. These areas have the most concentrated and severe forest loss in the entire UAMRYR and significantly impact the surrounding areas. Eighteen were secondary coordinate systems in the cities of Xiangyang, Jingmen, Yichang, Jingzhou, Yueyang, Yiyang Loudi, Heng-yang, Changde Yichun, Pingxiang, Xinyu, Ji'an, Fuzhou, Yingtan, Jiujiang, Jingdezhen, and Shangrao. While their degree and influence range of forest loss were less than that of the primary coordinate system, they had a particular ef-fect on nearby areas. In addition, there were 329 tertiary coordinate systems and 442 qua-ternary coordinate systems, both having far less influence and scope than the primary and secondary coordinate systems and most belonging to the coordinate systems in the first two levels.

We also added the figure 7 to illustrate the primary, secondary, tertiary, and quaternary coordinate systems.

 

11. Its hard to grasp that many information from fig 7. Which I believe can be better displayed as a table.

According to your comment, we replace the original Figure 7 with the Table 2. You can find it in the 3.3. Analysis of forest loss in important areas.

 

In addition to the above modifications, we have also proofread the full text and revised some improper statements. Once again, thank you very much for your good comments and suggestions which helped us a lot to improve the manuscript. If you have any other comments on this manuscript, we are very happy to follow your comments for further revision.

 

Kind regards.

 

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Dear author(s),

Thank you very much for taking the time to address my comments. I think all of the review comments had been addressed although I would like to apologize for my suggestion to change the figure into a table which resulted in a very long table (table 2).  Please revert it back to the figure format and keep the table 2 as the supplementary materials.

Author Response

Dear Reviewer:

 

Thank you very much for your valuable comments on our manuscript entitled “Study on Spatiotemporal Characteristic and Mechanism of Forest Loss in Urban Agglomeration in the Middle Reaches of the Yangtze River”. We revised the manuscript according to your comment. The Table 2 (very long table) was deleted, and the Figure. 9 (Original Figure. 7) was reverted back. The map legend of the Figure. 9 was revised also.

Once again, thank you very much for your good comments and suggestions which helped us a lot to improve the manuscript. If you have any other comments on this manuscript, we are very happy to follow your comments for further revision.

 

Kind regards and best wishes.

Author Response File: Author Response.docx