Spatial and Temporal Changes in Vegetation Cover in the Three North Protection Forest Project Area Supported by GEE Cloud Platform

Round 1

Reviewer 1 Report

Reviewer Comments

The manuscript entitled “Spatial and Temporal Changes of Vegetation Cover in the Three Northern Protection Forest Project Area Supported by GEE Cloud Platform” (ms forests-2156103) submitted to ‘Forests’ has been critically reviewed. The topic on Spatial and Temporal Changes of Vegetation Cover in the Three Northern Protection Forest Project Area is of great environmental, social and economic relevance and concern in the context of climate change. Though authors made modest efforts, however, ms needs minor revisions.

 

1.    In the title of the ms 'Forest Project Area' may be corrected as 'Forest Project Areas'.

2.    The introduction section may be slightly elaborated by referring the recent studies on MODIS data applications in vegetation dynamics.

3.    In line 96 the word “semi-arid and’ is repeated, it may be corrected.

4.    In the study area section brief on soils, mean annual rainfall and vegetation types may be described.

5.    In processing the time series MODIS data of 2000 to 2020 to minimize the atmospheric effect if any filtering techniques used in the study, it may be explained.  

6.    In Fig No. 1,3,5 and 12, the study area boundary and a few prominent place names may be given.

7.    The discussion and conclusion sections may be discussed separately for better clarity.

Author Response

Dear Reviewer,

Special thanks to you for your valuable comments and suggestions. Those comments are valuable and very helpful. We have read through comments carefully and have made corrections. Based on your submissions and suggestions, we revised and uploaded the manuscript. The manuscript is uploaded in Word and PDF versions. The modified part of the Word version is displayed in red to help you understand the changes to the manuscript. The PDF version is a complete version without trace, making it easier for you to read the manuscript.

We would love to thank you again for allowing us to resubmit a revised copy of the manuscript and we highly appreciate your time and consideration. All your comments and questions have been answered one by one in the responses below.  If you have any questions, please feel free to contact me. We sincerely look forward to communicating with you.

Best regards,

Mr. Xusheng Li

Author Response File: Author Response.docx

Reviewer 2 Report

First of all, I would like to note the high relevance of the study. Undoubtedly, the use of remote methods makes it possible to cover a large area of the study and to reveal the dependence of the area of vegetation cover on the main hydroclimatic predictors. The article is a complete study, minor improvements are required:

     1.There is little evidence about the reliability of the method chosen for the study, only two references (Based on NDVI data, the method of estimating vegetation cover using an image dichotomous model works well and there are many results [11, 12]), it would not hurt to add a few more works.

   2. Some pictures are hard to read, in particular Figure 12 (it is necessary to make a) and b)).

   3. Figure 13 has no semantic load in terms of demonstrating the dynamics from 2000 to 2020 (the lines are not clear, what is changing?)

Author Response

Dear Reviewer,

Special thanks to you for your valuable comments and suggestions. Those comments are valuable and very helpful. We have read through comments carefully and have made corrections. Based on your submissions and suggestions, we revised and uploaded the manuscript. The manuscript is uploaded in Word and PDF versions. The modified part of the Word version is displayed in red to help you understand the changes to the manuscript. The PDF version is a complete version without trace, making it easier for you to read the manuscript.

We would love to thank you again for allowing us to resubmit a revised copy of the manuscript and we highly appreciate your time and consideration. All your comments and questions have been answered one by one in the responses below.  If you have any questions, please feel free to contact me. We sincerely look forward to communicating with you.

Best regards,

Mr. Xusheng Li

Author Response File: Author Response.docx

Reviewer 3 Report

This paper deals with the investigation of the spatiotemporal changes in vegetation cover in a forest ecosystem using the google earth engine. The article is interesting and up-to-date and explores the use of a well-known cloud-based platform (Google earth engine). The main issues that need to be addressed/improved are the followings:

The introduction needs some improvements and to be extended adding recent literature relative to the article scope. For instance, some comments proposed are

-          Present some details/comments about the Gee platform. “The rise of cloud-processing systems, for instance, Google Earth Engine (GEE), providing free of charge access to EO datasets worldwide (Gorelick et al. 2017), is a promising factor for dynamic monitoring of forests.

 

1.       Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote sensing of Environment, 202, 18-27. https://doi.org/10.1016/j.rse.2017.06.031

 

-          Line 77. Present some examples of using GEE for vegetation cover changes using multi-temporal satellite imageries. For example, Stefanidis et al., 2022; examine temporal changes in vegetation cover in a peri-urban forest due to abiotic and biotic disturbances and their effects on erosion dynamics based on Landsat images. On the other hand, the GEE has been used for rapid vegetation cover due to wildfires and through burn area mapping and vegetation recovery (Gemitzi & Koutsias, 2022).

 

1.       Stefanidis, S., Alexandridis, V., & Mallinis, G. (2022). A cloud-based mapping approach for assessing spatiotemporal changes in erosion dynamics due to biotic and abiotic disturbances in a Mediterranean Peri-Urban Forest. Catena, 218, 106564. https://doi.org/10.1016/j.catena.2022.106564

 

2.       Gemitzi, A., & Koutsias, N. (2022). A Google Earth Engine code to estimate properties of vegetation phenology in fire-affected areas–A case study in North Evia wildfire event on August 2021. Remote Sensing Applications: Society and Environment, 26, 100720. https://doi.org/10.1016/j.rsase.2022.100720

 

 

-          Line 89. Clearly state the research gap and the novelty points of the approach.

-          Line 102.  Add some labels in the surrounding areas in figure 1. Also, improve legend fonts.

-          The style in the references is not appropriate.

 

 

 

 

 

Author Response

Dear Reviewer,

Special thanks to you for your valuable comments and suggestions. Those comments are valuable and very helpful. We have read through comments carefully and have made corrections. Based on your submissions and suggestions, we revised and uploaded the manuscript. The manuscript is uploaded in Word and PDF versions. The modified part of the Word version is displayed in red to help you understand the changes to the manuscript. The PDF version is a complete version without trace, making it easier for you to read the manuscript.

We would love to thank you again for allowing us to resubmit a revised copy of the manuscript and we highly appreciate your time and consideration. All your comments and questions have been answered one by one in the responses below.  If you have any questions, please feel free to contact me. We sincerely look forward to communicating with you.

Best regards,

Mr. Xusheng Li

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

The article can now published to the journal as all comments addressed.