Next Article in Journal
Exploring PlanetScope Satellite Capabilities for Soil Salinity Estimation and Mapping in Arid Regions Oases
Next Article in Special Issue
Domain Hybrid Day-Ahead Solar Radiation Forecasting Scheme
Previous Article in Journal
Using Nighttime Lights Data to Assess the Resumption of Religious and Socioeconomic Activities Post-COVID-19
Previous Article in Special Issue
Solar Potential Uncertainty in Building Rooftops as a Function of Digital Surface Model Accuracy
 
 
Article
Peer-Review Record

Estimation of Perceived Temperature of Road Workers Using Radiation and Meteorological Observation Data

Remote Sens. 2023, 15(4), 1065; https://doi.org/10.3390/rs15041065
by Hankyung Lee, Hyuk-Gi Kwon, Sukhee Ahn, Hojin Yang and Chaeyeon Yi *
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Remote Sens. 2023, 15(4), 1065; https://doi.org/10.3390/rs15041065
Submission received: 25 November 2022 / Revised: 13 February 2023 / Accepted: 13 February 2023 / Published: 15 February 2023
(This article belongs to the Special Issue New Challenges in Solar Radiation, Modeling and Remote Sensing)

Round 1

Reviewer 1 Report

attached review material

Comments for author File: Comments.pdf

Author Response

Please refer to the attachment. 

Author Response File: Author Response.pdf

Reviewer 2 Report

Summary:

In this article, the authors report the results of a study that combined real-world radiation and meteorological data from two Korean road locations and a weather station location with worker-relevant group data and modeling approaches to: #1) compare radiation and meteorological observations for asphalt and concrete road conditions on sunny and cloudy days; and #2) develop a tailored model of perceived temperature (PT), which incorporates environmental measures and other elements of human heat budget relevant to workers, including clothing and workload. This study provides a commendably detailed series of results on radiation and meteorological observations in the different locations and conditions. However, there are no statistical analyses presented to support the first aim (#1) comparison results. The implications of the latter aim (#2) could be strengthened with discussion of the contextual literature on the relationship between PT and actual human heat health outcomes or adaptation behavior data. It is therefore somewhat difficult to evaluate the significance of the findings and their potential ultimate implications for preventing adverse heat-related outcomes among road workers.

 

Major comments:

1)    I am not as familiar with the PT models as with heat stress assessment approaches and guidelines based on WBGT (e.g., NIOSH, ACGIH, ISO), for which there is a literature on the relationship between WBGT and human heat illness. While the approach to PT makes sense (e.g., incorporating environmental measures and other elements of human heat budget relevant to workers, including clothing and workload), is there any literature to suggest an association between PT and actual human heat health outcomes or adaptation behaviors? If so, it would strengthen the implications of this work to include mention of this literature in the introduction.

2)    As far as I can tell, there is not a formal statistical comparison of various differences in exposure and PT reported between concrete and asphalt on sunny and cloudy days. If this is indeed a main aim of the study, statistical comparisons would be helpful.  If not, consider moving this analysis to Supplemental Materials and focusing the main manuscript on the PT estimation model development, results, and implications.

3)      The Discussion section is quite short. The Conclusions section is lengthy and somewhat of a high-level rehash of the methods and results. While some limitations are mentioned, there is no Limitations subsection. Suggest lengthening the Discussion with more tie-in with the existing literature, adding a ‘Strengths & Limitations’ subsection with information about the strengths and limitations of the study, and making the Conclusions section more concise, highlighting potential implications. What does this study add to the literature, and what are the limitations? Can more detail be provided about how the information from this study will be used to inform response measures and policies in real-world road work settings in Korea to protect workers from heat stress? Is this study generalizable to other geographical areas and settings?

 

Minor comments:

1)    Abstract, Page 1, line 7: People cannot be exposed to heat stroke (an illness).  Rather, people can be exposed to heat stress (the combined heat exposure from ambient heat, clothing, and workload), which can lead to heat-related illness (including heat stroke) and its consequences.  Same comment for Introduction, Page 2, line 46.

2)    Methods, Page 5, Table 1: Is it possible to report the accuracy (not just the measurement range) of the mobile meteorological observation device in the Table?

3)    Methods, Page 1, Lines 145-148: What are the implications of making the sky view factor observations only once a day, even though cloud conditions vary throughout the day? Is this a limitation of the study?

4)    Discussion, Pages 24-25, Lines 572-577: The authors mention that measurements at the concrete and asphalt site were not made on the same days due to limitations on the amount of available equipment. Is it possible to account for this lack of temporally concurrent measurement in the analysis, particularly within statistical models that compare road and sun/cloud conditions? What are the potential implications of this limitation on the results?

Author Response

Please refer to the attachment. 

Author Response File: Author Response.pdf

Reviewer 3 Report


Comments for author File: Comments.pdf

Author Response

Please refer to the attachment. 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

General : I realize that the authors revised the manuscript significantly and all my comments and suggestions were properly addressed in the revised manuscript. So, I do not have more critical comments for consideration.

Minor : 

Fig 11 : (b) line graph cannot be resolved due to PDF converting problem(?). Also, you may present a Figure caption and a)~d) labels succinctly for a better illustration of the details. The a)~d) are included MRT snapshot ( time ? or daily mean ) and temporal variation of MRT.

Fig 12 : Cases (Sunny and Cloudy ) in Figure express explicitly included date for the reader.

English needs improvement.

Author Response

We thank you for your thoughtful suggestions and insights.
The manuscript has benefited from these insightful suggestions
The manuscript has been rechecked and the necessary changes have been made in accordance with the reviewers’ suggestions. 
I submit the final version of the English improvement completed.
Thank you again for the review comment.

Reviewer 3 Report

After the authors' replly to my comments, I consider that the paper can be published

Author Response

We thank you for your thoughtful suggestions and insights.
The manuscript has benefited from these insightful suggestions
The manuscript has been rechecked and the necessary changes have been made in accordance with the reviewers’ suggestions. 
I submit the final version of the English improvement completed.
Thank you again for the review comment.

Back to TopTop