Leveraging Gaussian Processes in Remote Sensing

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The authors give a review on the application of Gaussian process and machine learning in remote sensing. Some detailed questions should be issued, they are listed as:

1.     The abstract needs to be modified. The author should further clarify the advantages of applying Gaussian processes in the field of remote sensing.

2.     It is suggested to review and more articles in related fields.

3.     A review should pay attention to the logical coherence of the entire paper.

Comments on the Quality of English Language

 Minor editing of English language required.

Author Response

Thank you very much for taking the the time to review my submission! I appreciate your comments and look forward to improving my work.

Comment 1: The abstract needs to be modified. The author should further clarify the advantages of applying Gaussian processes in the field of remote sensing.

Response 1: I added more language to acknowledge the performance of Gaussian processes in the review to clarify the advantage and added more information regarding the project this pertains to. Changes are indicated in red.

Power grid reliability is crucial to supporting critical infrastructure, but monitoring and maintenance activities are expensive and sometimes dangerous. Monitoring the power grid involves diverse sources of data including that inherent to the power operation (inertia, damping, etc.) and ambient atmospheric weather data. The Autonomous Intelligence Measurements and Sensor Systems (AIMS) project at the Oak Ridge National Laboratory is a project to develop a machine-controlled response team capable of autonomous inspection and reporting with the explicit goal of improved grid reliability. Gaussian processes (GPs) are a well-established Bayesian method for analyzing data. GPs have been successful in satellite sensing for physical parameter estimation and the use of drones for remote sensing is becoming increasingly common. However, the computational complexity of GPs limits their scalability. This is a challenge when dealing with remote sensing datasets, where acquiring large amounts of data is common. Alternatively, traditional machine learning methods perform quickly and accurately, but lack the generalizability innate to GPs. The main objective of this review is to gather burgeoning research that leverages Gaussian processes and machine learning in remote sensing applications to assess the current state of the research. The contributions of these works show that GP methods have superior model performance in satellite and drone applications. However, more research using drone technology is necessary. Furthermore, there is not a clear consensus on methods are the best for reducing computational complexity. This review paves out several routes for further research as part of the AIMS project.

Comment 2:  It is suggested to review and more articles in related fields.

Response 2: Most of the articles reviewed are quite current, and I have not seen new publications in using Gaussian processes in remote sensing in a power grid application that I think are relevant enough to be added. In general, I did include sources that applied to other areas outside the power grid as long as remote sensing was involved, but I don't want to add others that are not relevant to the special issue.

Comment 3:  A review should pay attention to the logical coherence of the entire paper.

Response 3 : I have added transitional paragraphs and a breakdown of the order of the paper. I have split the Gaussian Processes section into two parts, and added a section on computational complexity at the advice of other reviewers.

Reviewer 2 Report

Comments and Suggestions for Authors

I have uploaded the comments for authors with an attachment.

Comments for author File: Comments.docx

Author Response

Thank you for taking the time to review my submission! I appreciate your comments and look forward to improving my work.

Comment 1: The overall content of the article is reasonable, but I think it is better to write the first part of the introduction into two parts, one part of the overview background, the other part of the definition.

Response 1: I split the Gaussian Processes section into two parts to highlight the definition and the advantages. I also added a section on computational complexity at the advice of another reviewer.

Comment 2: In p4, line 148, “(P.)”should be revised to “(P).)”.

Response 2: The authors of that article use the abbreviation "(P.)," so I am going to leave it consistent with the original article.

Comment 3: Please adjust the format of the related images in this article.

Response 3: Can you clarify what adjustment is necessary? I believe they are formatted according to the template.

Comment 4: In this article, it would be better if the author could add corresponding practical examples to illustrate.

Response 4: I have added more language describing the project this research pertains to as well as adding examples on how the research could be used in the project.

Comment 5: Keep the reference format consistent.

Response 5: I have checked through references and made changes so that the format is consistent.

  

Reviewer 3 Report

Comments and Suggestions for Authors

1.The abstract lacks a clear explanation of the core content of the paper, and the content is somewhat lengthy, with a large amount of information but not enough concentration, making it difficult for readers to grasp the key points. Although the application of Gaussian processes and machine learning in remote sensing was mentioned, the main objectives and contributions of the paper were not clearly stated. It is recommended to clearly state in the abstract which applications of Gaussian processes in remote sensing are summarized in this article, as well as the specific advantages and disadvantages of these applications.

2.The introduction section is relatively lengthy and lacks emphasis. The introduction extensively discusses the importance of power grid reliability, but it is less directly related to the application of Gaussian processes in remote sensing. More emphasis should be placed on the unique advantages and specific application scenarios of Gaussian processes in power grid monitoring.

3.The introduction section does not clearly explain the structure and organization of this article. Suggest briefly summarizing the structure of the paper at the end of the introduction to facilitate reader understanding.

4.There is no detailed solution to the computational complexity of Gaussian processes. Although the issue of computational complexity in Gaussian processes has been mentioned, there is a lack of specific solutions or improvement methods. Discussions on how to deal with computational complexity should be increased, and existing research methods and their effectiveness should be listed.

5.The chapter arrangement can be more compact. The connection between chapters is relatively loose. It is recommended to add transitional paragraphs between each chapter to explain the connection and logical relationship of the content in each section.

6.The explanation of the chart is not detailed enough, and the specific content and significance of the chart are not explained in detail. Detailed explanations of the charts should be added to enable readers to better understand the content of the charts.

7.The conclusion section needs to be strengthened. The conclusion section did not fully summarize the main findings and contributions of the review, nor did it propose specific directions for future research. Summarize the main findings of the review and propose specific suggestions and directions for future research.

Comments on the Quality of English Language

1.The abstract lacks a clear explanation of the core content of the paper, and the content is somewhat lengthy, with a large amount of information but not enough concentration, making it difficult for readers to grasp the key points. Although the application of Gaussian processes and machine learning in remote sensing was mentioned, the main objectives and contributions of the paper were not clearly stated. It is recommended to clearly state in the abstract which applications of Gaussian processes in remote sensing are summarized in this article, as well as the specific advantages and disadvantages of these applications.

2.The introduction section is relatively lengthy and lacks emphasis. The introduction extensively discusses the importance of power grid reliability, but it is less directly related to the application of Gaussian processes in remote sensing. More emphasis should be placed on the unique advantages and specific application scenarios of Gaussian processes in power grid monitoring.

3.The introduction section does not clearly explain the structure and organization of this article. Suggest briefly summarizing the structure of the paper at the end of the introduction to facilitate reader understanding.

4.There is no detailed solution to the computational complexity of Gaussian processes. Although the issue of computational complexity in Gaussian processes has been mentioned, there is a lack of specific solutions or improvement methods. Discussions on how to deal with computational complexity should be increased, and existing research methods and their effectiveness should be listed.

5.The chapter arrangement can be more compact. The connection between chapters is relatively loose. It is recommended to add transitional paragraphs between each chapter to explain the connection and logical relationship of the content in each section.

6.The explanation of the chart is not detailed enough, and the specific content and significance of the chart are not explained in detail. Detailed explanations of the charts should be added to enable readers to better understand the content of the charts.

7.The conclusion section needs to be strengthened. The conclusion section did not fully summarize the main findings and contributions of the review, nor did it propose specific directions for future research. Summarize the main findings of the review and propose specific suggestions and directions for future research

Author Response

Thank you for taking the time to review my submission! I appreciate your comments and look forward to improving.

Comment 1: The abstract lacks a clear explanation of the core content of the paper, and the content is somewhat lengthy, with a large amount of information but not enough concentration, making it difficult for readers to grasp the key points. Although the application of Gaussian processes and machine learning in remote sensing was mentioned, the main objectives and contributions of the paper were not clearly stated. It is recommended to clearly state in the abstract which applications of Gaussian processes in remote sensing are summarized in this article, as well as the specific advantages and disadvantages of these applications.

Response 1: I have added more language describing the applications of Gaussian processes and how the current project of interest relates. I have also stated the main objective of the paper.

Comment 2: The introduction section is relatively lengthy and lacks emphasis. The introduction extensively discusses the importance of power grid reliability, but it is less directly related to the application of Gaussian processes in remote sensing. More emphasis should be placed on the unique advantages and specific application scenarios of Gaussian processes in power grid monitoring.

Response 2: I have added more information on the application scenario as well as the motivation for using Gaussian processes.

Comment 3: The introduction section does not clearly explain the structure and organization of this article. Suggest briefly summarizing the structure of the paper at the end of the introduction to facilitate reader understanding.

Response 3: I have added language to breakdown the structure of the paper.

Comment 4: There is no detailed solution to the computational complexity of Gaussian processes. Although the issue of computational complexity in Gaussian processes has been mentioned, there is a lack of specific solutions or improvement methods. Discussions on how to deal with computational complexity should be increased, and existing research methods and their effectiveness should be listed.

Response 4: I have added a section briefly describing methods that address computational complexity. I think a detailed solution is outside the scope of this review. Several of the articles that use these methods successfully are described in the body of the paper.

Comment 5: The chapter arrangement can be more compact. The connection between chapters is relatively loose. It is recommended to add transitional paragraphs between each chapter to explain the connection and logical relationship of the content in each section.

Response 5: I have added transitional paragraphs and condensed the number of the chapters.

Comment 6: The explanation of the chart is not detailed enough, and the specific content and significance of the chart are not explained in detail. Detailed explanations of the charts should be added to enable readers to better understand the content of the charts.

Response 6: I have added more detailed explanations in the chart descriptions.

Comment 7: The conclusion section needs to be strengthened. The conclusion section did not fully summarize the main findings and contributions of the review, nor did it propose specific directions for future research. Summarize the main findings of the review and propose specific suggestions and directions for future research.

Response 7: I have added more summary language in the conclusion and added specific areas of future work.

 

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

The author has not marked the changes in the manuscript, so it is impossible to check what is modified or not, and there are no references in the paper.

Comments on the Quality of English Language

The author has not marked the changes in the manuscript, so it is impossible to check what is modified or not, and there are no references in the paper.

Author Response

Comment 1: The author has not marked the changes in the manuscript, so it is impossible to check what is modified or not, and there are no references in the paper.

Response 1: Apologies, I thought the responses were sufficient. The new additions are marked with blue text in the re-submitted manuscript. The references have been corrected.

Round 3

Reviewer 3 Report

Comments and Suggestions for Authors

The author addresses the issues raised and therefore proposes publication.

Comments on the Quality of English Language

The author addresses the issues raised and therefore proposes publication.