PONE-D-23-19311Improved prediction of hiking speeds using a data driven approachPLOS ONE

Dear Dr. Wood,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This research centers on the prediction of hiking speed using a novel generalized linear model. By integrating public GPS data, this model has the ability to forecast walking speed by considering the gradient of the terrain (hill slope) and the degree of terrain obstruction. Despite the announcement of substantial improvement compared to various established models, there are several revisions that need to be addressed first.

1. The methods of the paper need further clarification. First, detailed descriptions of the data and data processing should be included in the main body of the paper, rather than in the Supporting Information, as this is a paper focusing on a data-driven approach. This leads to the structure of the paper being fragmented and some terminologies sound wired and confusing. For instance, what is meant by "datapoint" mentioned in line 152?

2. Additionally, more details regarding the Generalised Linear Model, which forms the foundation of the research, should be provided. Questions that need to be addressed include: What are the inputs? How are these variables organized? What is the relationship between variables a, b, c, d and the results presented in Table 1? How does the critical gradient affect the performance of the model? Are the speed and characteristics aggregated at a point level or in line string segments?

3. The introduction section of the document is excessively lengthy and would benefit from a reorganization of its content. I suggest incorporating some of the introductory material about the hiking speed model into the methods section. Furthermore, the introductory material concerning the hiking speed model should be summarized (in introduction section) and present the formulations instead of listing various models and qualitatively describe these models (in method section). This will facilitate the comprehension of the paper.

4. Considering that the model utilizes multiple variables and employs GLM for regression, the improvement achieved by the model is not as significant, which could potentially impact its practical application. While the model is expected to outperform rule-based models that do not fit the empirical data in previous studies, I have reservations about its applicability in real-life scenarios. The author should provide more details about the results and discuss the implications of these performance changes on hiking activities.

5. In terms of the conclusion, the research should interpret the social implications of the findings derived from the data. The importance of hiking speed estimations and the contributions of the paper should be emphasized in both introduction and conclusion.

Reviewer #2: Summary

In this paper, Wood et al. propose a new set of equations for predicting travel rates as a function of landscape conditions. Whereas several functions exist for the prediction of rates driven by walking slope (slope in the direction of pedestrian travel), few take into consideration the hill slope (slope in the direction of the terrain’s steepest descent) and/or the presence of terrain obstructions above the ground surface. Wood et al. incorporate both of these two characteristics, finding significant effects of each and providing novel quantitative insight that could be valuable for more robust travel rate predictions, particularly in off-road/off-trail environments. The paper is well presented, and the topic is of wide interdisciplinary interest – well-suited for PLOS ONE. I have a few major and minor concerns that I believe should be addressed prior to publication, but I do believe the work will eventually be a valuable contribution to the existing literature.

Major Comments

- It seems terrain obstructions could be handled in a more elegant way. Simply using height in a binary fashion as the basis of determining off-road impedance seems like a missed opportunity. Height is definitely one important consideration (it’s easier to step over short vegetation than tall vegetation), but density is another arguably more important one. One can easily walk through tall but sparse vegetation just as one can easily walk through short but dense vegetation. Some focal measure of density (e.g., the number of lidar-derived pixels above a certain height threshold within a given neighborhood) would be worth examining.

- I would like to see comparisons to more existing travel rate functions. Several papers have already demonstrated superiority over Tobler and Naismith. To ensure that this work truly represents a valuable contribution to the literature requires comparisons to more contemporary algorithms. Although it’s not necessarily the most important statistical measure of model performance in the context of GLMs, an R-squared value of 0.09 does not leave the reader with a high degree of confidence in your new model.

- Related to the point above, you point out the travel rates are largely just a means to getting at a more useful measure in travel time. You provide several examples about the importance of estimating travel time. Can you demonstrate how your new algorithm provides an opportunity for the accurate estimation of travel time? I think the results would look a lot better than your travel rate estimates, since predicting time over a longer hike should have smaller margins of error than instantaneous travel rates derived from erroneous GNSS data.

- I think a lot of valuable information that could be included in the main manuscript is placed in the supplementary materials. For example, the main manuscript does not have any depiction of the final function forms (line plots of speed vs. slope, e.g., S4 Fig 3), which seems like an important omission. Also S3 Fig 1 provides really useful insight into the complexity of trying to predict travel rates, given the extreme variability in the data.

Minor Comments

L4: Extremely minor point but I’m not sure I would consider it “standard practice”, per se. It’s certainly *good* practice.

L2-8: You begin the paragraph stating that travel rates are important in “many situations” and then only proceed to give one example. You might consider adding more to frame the importance of your study.

L14-15: I appreciate the split into individual and external factors, but to say that the effects of slope, for example, “will be consistent across all individuals” isn’t true. Slope, and other landscape conditions, affects people very differently.

L2-23: The first three paragraphs have not a single reference to existing literature. I’ll grant you that a lot of the discussion up to this point is based on intuition/experience, but there are several statements that would carry more weight with references to existing studies.

L33-34: I don’t understand this statement. Are you suggesting that Naismith’s rule does not account for slope? That’s *precisely* what Naismith’s rule does… Please clarify/rephrase.

L67: very different situations than what?

L84 and throughout: You might consider the more universal term of global navigation satellite systems (GNSS) rather than the US-specific Global Positioning System (GPS)

L94 and elsewhere: It seems you should define “terrain obstruction” explicitly. I assume this means the presence of vegetation, primarily? But I could also imagine a cliff being considered a terrain obstruction.

Figure 2 caption: should read “can *be* identified”

L145-151: So speeds are based solely on time between sequential GNSS positions and the timing of those same positions? Wouldn’t this provide an underestimate of speeds? I’m picturing a windy, zig-zagging trail… If a GNSS position is only recorded every, say, 30 seconds, then the resulting “track” may appear to move straight through the zigzags, giving an underestimate of the distance actually traveled.

L174: more important than the version of RStudio (simply the IDE) is the version of R

S2

In the Break Finding section, about 2/3 through the second paragraph, you say “…paused recording for a break – example here”. Is this an error?

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Reviewer #1: No

Reviewer #2: No

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PONE-D-23-19311R1Improved prediction of hiking speeds using a data driven approachPLOS ONE

Dear Dr. Wood,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Nov 23 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Yuxia Wang

Academic Editor

PLOS ONE

Additional Editor Comments:

Dear Authors,

We received two reviews of your manuscript. While Reviewer #2 recommended acceptance, Reviewer #1 pointed some significant concerns which need to be addressed. Therefore, I would like to suggestion a major revision. During the revision, please pay attention to the suggestion and comments of Reviewer #1. Please note that your revised version will be further assessed by external reviewers.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: (No Response)

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The revised version of the paper has undergone substantial improvements in terms of its writing, logic, and clarity. However, there remain some significant concerns that, in my opinion, should be addressed before publication.

Statistical Significance of Model Improvement: One critical concern, previously highlighted in the last round of review comments, pertains to the practical significance of the model's performance. Given that the model incorporates multiple variables and employs Generalized Linear Models (GLM) for regression, the reported improvement achieved by the model appears to be modest. This issue has also been noted by other reviewers, particularly concerning the low R-squared value of 0.09. The authors should not overlook this concern and should provide a more thorough discussion of the model's practical utility and limitations.

Detailed Presentation of Data-Driven Approach: As the paper focuses on a data-driven approach to modeling walking speed, it would greatly enhance the understanding of the methodology if the authors provided more quantitative characteristics of the original data. For instance, Figure 3 illustrates walking speed predictions under various terrain conditions. It is essential to include statistical characteristics of the actual speed data (e.g., average, standard deviation, or the 95% confidence interval) when individuals are traversing different types of terrain, derived from real datasets. Additionally, incorporating statistical characteristics of the ground truth data in Figure 4 would strengthen the paper's credibility and the evaluation of the model's performance.

Transparency in Exclusion of Data Points: It would be beneficial for readers to know the number and percentage of data points or sections that were excluded due to the filtering process. This transparency will provide a clearer picture of the data selection and processing steps.

Additional Minor Comments:

Introduction References: In the introduction section, consider providing more references when discussing the classification of factors that can impact walking speed into two groups. This will enhance the depth of the literature review and provide a stronger foundation for your work.

Model Performance Evaluation: Highlighting the fact that the model's performance evaluations are conducted at the section level should be done earlier in the paper to prevent any misunderstanding. Additionally, consider presenting statistical characteristics of the sections, such as their length and the distribution of slopes, to provide a comprehensive assessment.

Clarify Terminology: Distinguish between "hill slope" and "walking slope" throughout the paper to avoid confusion. For instance, in the caption for Figure 3, specify the meaning of "slope" in Figures 3A and 3B to enhance clarity for readers.

Overall, while the revisions have improved the paper's quality, addressing these concerns and making the suggested enhancements will further enhance the paper's scientific rigor and comprehensibility.

Reviewer #2: I thank the authors for addressing my comments thoroughly and am happy to recommend that this revised version be accepted for publication. It will be a valuable contribution to the literature.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

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[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Improved prediction of hiking speeds using a data driven approach

PONE-D-23-19311R2

Dear Dr. Wood,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Yuxia Wang

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I thank the authors for addressing my comments thoroughly and am happy to recommend that this revised version be accepted for publication.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

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