Estimating Fire Radiative Energy Density with Repeat-Pass Aerial Thermal-Infrared Imaging of Actively Progressing Wildfires

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This study explores the estimation of fire radiative energy density using repeat-pass aerial thermal infrared imaging to better understand wildfire behavior variables for more effective planning and response strategies. Some comments and suggestions are raised as follows.

 

Comments and suggestions:

1. The article examined the correlation between FRED and FRFD time series shape alteration, however, there is insufficient actual data for the time series. We suggest to provide additional FRFD time series shape data to strengthen the credibility of the article's findings.

 

2. The article employs similar analytical methodologies as previous studies, but utilizes distinct datasets for large-scale fires compared to others. Please compare the conclusions drawn in this article with those of previous research and highlight the disparities in conclusions derived from data obtained from actual large fires versus data acquired from laboratory fire simulations.

 

3. The combustion process of large scale wildfire will generate a significant amount of water vapor and ash, which has a substantial influence on the infrared detection of the fire surface within the atmosphere. This impact cannot be overlooked, yet the test data in this paper disregarded it. We recommend providing additional explanations or implementing necessary modifications.

 

Comments on the Quality of English Language

Minor editing of English language required

Author Response

The article examined the correlation between FRED and FRFD time series shape alteration, however, there is insufficient actual data for the time series. We suggest to provide additional FRFD time series shape data to strengthen the credibility of the article's findings.

Thank you for the input on our time series data. The temporal duration of our time series data is limited due to cost and logistic realities of experimental research involving aerial imaging missions. The airborne imaging system is capable of sequential imaging of an actively progressing fire front every 5 minutes or more, and can only collect imagery for 3-4 hours before refueling. Despite these constraints our sample size is extensive, we are still able to properly reconstruct time series that we can use for fire intensity estimation, which has also been exhibited for controlled fires (Hudak et al. 2016; 2018) and actively progressing wildfires (Riggan et al. 2004).

Since our sampling extent was quite large (landscape scale wildfire) we had a large number of time series to analyze and work with for two days of an actively progressing fire (Thomas Fire), In total we analyzed > 24,000 profiles for fire intensity time series analysis and cumulative fire intensity calculation. For decay modeling, we used 20,000 FRFD temporal profiles, and for obscuration adjustments using or decay models, we used 4,000 number of FRFD temporal profiles. For novel experimental research like this, we feel that the data sets are extensive and more than appropriate for addressing our research questions. As far as we are aware, not other experimental missions have been conducted that would provide appropriate data sets.

The article employs similar analytical methodologies as previous studies, but utilizes distinct datasets for large-scale fires compared to others. Please compare the conclusions drawn in this article with those of previous research and highlight the disparities in conclusions derived from data obtained from actual large fires versus data acquired from laboratory fire simulations

This is certainly a key component that we wish to address, however the literature lacks comparable studies since airborne thermal infrared imagery of actively progressing wildfires is not collected frequently (at least for the purpose of academic research). The imagery from Riggan et al. 2004 was collected for wildfires actively progressing through Brazilian forests, so comparable are hard to come by.

In the case of field-controlled experiments, we compared our results to the works of Hudak et al. 2016;2018, since they employed similar methods for their fire intensity calculations. In addition, we compare the temporal shape of our FRFD time series to the time series proposed by Alexander 1998 through our exponential decay modeling. 

The combustion process of large scale wildfire will generate a significant amount of water vapor and ash, which has a substantial influence on the infrared detection of the fire surface within the atmosphere. This impact cannot be overlooked, yet the test data in this paper disregarded it. We recommend providing additional explanations or implementing necessary modifications.

We appreciate you mentioning your concerns for water vapor and ash impacting our measurements. Our article addresses and provides two potential solutions to the problem, so the claim that this impact is overlooked and disregarded is false.

First, we proposed an ash adjustment by subtracting a larger value (343 K, as identified by Riggan et al. 2000) near the end of the time series after flaming combustion is assumed to be finished. This temperature is 473K, the minimum temperature for chaparral to combust, as identified by Engstrom et al. 2004. The adjustment is a piecewise function that is applied after the peak temperature has been reached for the FRFD time series.

For addressing the potential influence of obscurations, we developed a binary classifier that would identify notable instances of large increases and decreases in flux density measurements post peak. Using this classifier, we assume the sharp decrease and increase is an instance at which water vapor or particles are obscuring thermal infrared radiation. We used this binary classifier to remove profiles from our exponential decay modeling analysis, and a method to identify profiles that can be adjusted through exponential decay model smoothing.

We acknowledge that additional research that involves a more nuanced approach towards identifying obscurations, or providing a more thorough determination of how impactful ash depositions are on our thermal infrared readings. We take note of this in our discussion, when we mention that variation in ash color may influence the impact of ash on our thermal infrared measurements. But both concerns are directly mentioned and addressed in our article.

 

 

 

 

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you for your well-thought out and interesting research. The article was well written and very informative.

I only have a couple of minor suggestions:

End of second paragraph in intro: There are some examples of fire behavior models that include a limited number of field experiments and wildfire observations. These focus on rate of spread, which is not your main focus, but it may be worth clarifying this sentence. e.g.

https://doi.org/10.1071/WF21068

https://doi.org/10.1016/j.foreco.2012.06.012

 

The final sentence in section 2.1 appears to be a repeat.

 

There is a repeat date in section 2.7: To assess the impact of fire front proximity to measured FREDs and FRFDs, we identified four locations (two for 8 8 December and two for 9 December sequences) across fire fronts delineated by Schag et al [18].

Author Response

There are some examples of fire behavior models that include a limited number of field experiments and wildfire observations. These focus on rate of spread, which is not your main focus, but it may be worth clarifying this sentence. e.g.

Thank you for the encouraging words and the suggestions for articles to include. It’s often difficult to comb through all the literature, so we appreciate the references so that our article is as well researched and notated as possible. We added references accordingly on page 1 (Introduction).

We also addressed the repeats you mentioned in the methods section. Thank you for identifying them!

Reviewer 3 Report

Comments and Suggestions for Authors

Estimating fire radiative energy density with repeat-pass aerial thermal infrared imaging of actively progressing wildfires

Dear Authors,

The subject of the paper is a current and very important topic since it is a contribution to the study of wildfires. In my opinion, the subject fits the scope of the Fire Journal.

The paper addresses procedures and their sensitivity and reliability for reconstructing time sequences of TIR flux densities and estimating FRED for active wildland fires through aerial thermal infrared imagery at a landscape scale.

 

Main Remarks:

- In my opinion, the document is not well written. The text is not formatted and has typographical errors.

- Conclusions are mixed with the discussion of results. Conclusions should appear in their own section and not mixed with the discussion of results.

- Throughout the text the authors frequently write (we did...). This type of writing is not appropriate for a scientific text.

- Several sentences begin with "But..." which is not correct.

 

In my opinion, the document deserves to be published, but the text must be reviewed in detail.

Author Response

In my opinion, the document is not well written. The text is not formatted and has typographical errors.

Thank you for addressing the readability of our article. We want this article to be as informative as possible, especially because we consider our findings to be important for the literature and compelling. The reviewer does not provide examples of what is not well written nor typographical errors. All of the co-authors are native English speakers and have reviewed and edited the manuscript multiple times at various stages of writing. We took another editing pass based on the reviewer’s comments and made a few revisions. These revisions were made for pages 1 and 2.

Conclusions are mixed with the discussion of results. Conclusions should appear in their own section and not mixed with the discussion of results.

Thank you for this suggestion. We have separated the two sections, The conclusion section is now located on page 22

Throughout the text the authors frequently write (we did...). This type of writing is not appropriate for a scientific text.

We disagree with this assessment. Many if not most scientific journals have moved towards use of active voice/first person. If Fire MDPI editors disagree with our assessment we would be fine with modifying the text.

Several sentences begin with "But..." which is not correct.

Thank you, We modified all instances of sentences starting with “But.”

 

 

 

 

 

 

 

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The article has been well improved via adding more explanations for the issues what I concerned. However, there is still one question which is listed as follows. So I suggest that this paper can be accepted and published in this journal after minor changes.

Question: The author mentioned in the response that there were sufficient sampling sizes in the study, including 20,000 FRFD temporal profiles used for decay modeling and 4,000 FRFD temporal profiles used for obscuration adjustments. However, these details were not elaborated on in the article. We suggest that more relevant explanations and descriptions should be supplemented in the text.

Author Response

Question: The author mentioned in the response that there were sufficient sampling sizes in the study, including 20,000 FRFD temporal profiles used for decay modeling and 4,000 FRFD temporal profiles used for obscuration adjustments. However, these details were not elaborated on in the article. We suggest that more relevant explanations and descriptions should be supplemented in the text.

Thank you for the question. We provided the specific numbers in the results sections to provide a clearer description of the total number of profiles we analyzed.

Reviewer 3 Report

Comments and Suggestions for Authors

Dear Authors,

Thank you very much for your responses to my comments and for the text corrections.

Author Response

Thank you for your input throughout the peer review process!