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Peer-Review Record

A Control-Theoretic Spatio-Temporal Model for Wildfire Smoke Propagation Using UAV-Based Air Pollutant Measurements

by Prabhash Ragbir 1, Ajith Kaduwela 2, Xiaodong Lan 3, Adam Watts 4 and Zhaodan Kong 1,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3:
Submission received: 1 February 2024 / Revised: 27 March 2024 / Accepted: 18 April 2024 / Published: 24 April 2024
(This article belongs to the Topic Application of Remote Sensing in Forest Fire)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Review attached. Thanks!

Comments for author File: Comments.pdf

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript focused on developing a data-driven, spatiotemporal model for predicting smoke plume dynamics in both space and time. Overall, this paper is not suitable for the journal’s scope. However, there are a few suggestions for improving this paper.

The abstract could be restructured to follow a logical flow, starting with the problem statement, then the proposed approach, the evaluation or results, and concluding with the main findings or implications.

Providing a brief introduction or background information on the significance of early wildfire detection would be beneficial. Explain why early detection is crucial in mitigating the negative impacts of wildfires and how current methods may have limitations.

The authors should clearly provide the study's main objective or research question. This will help readers understand the specific problem the research aims to address and the paper's contribution.

What sets this research apart from previous work in the field? What new insights, methods, or approaches does it bring?

In Figure 1, the authors should indicate the air quality sensor package.

The authors should explain how to use model-based controllers for early wildfire detection.

Instead of stating that the model showed good performance and outperformed the Gaussian puff model, provide specific metrics or results to support these claims. This will add credibility to the findings and give readers a better understanding of the model's effectiveness.

Comments on the Quality of English Language

n/a

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This paper presented a new model for predicting the CO2 propagation-based UAV collecting data of wildfire scenarios. The proposed model uses a spatiotemporal model based on the SID method. Then, the comparison between SID and GPM was shown where the SID outperformed than GPM. Nevertheless, we have some comments to fulfill the paper as follows:

1. please refer is [1]-[5] instead of [1] [2]...[5] at line no.32, and [6]-[7] line no. 42, line 61, and another as related.

2. How about the wind speed during the testing? 

3. How is the speed of wind from the propeller of the octocopter? Have any effect on the sensory board on UAV when used?   

4. Why consider the GPM for UAV? Because it might not be suitable for mobile sensing stations. Please discuss and show any possible information.    

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have adequately addressed my review comments. 

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript has been qualified by the comments and discussion. The paper soundness is better quality than the previous version. Then, I have no comment and agree for acceptable of the paper. 

Thank you, 

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