Study on air temperature estimation and its influencing factors in a complex mountainous area

Wang Runke; You Xiaoni; Shi Yaya; Wu Chengyong; Liu Baokang

doi:10.1371/journal.pone.0272946

Peer Review History

Original SubmissionApril 4, 2022
1 May 2022 Decision Letter - Ming Luo, Editor PONE-D-22-09843Study on air temperature estimation and its influencing factors in a complex mountainous areaPLOS ONE Dear Dr. Wang, 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 Jun 15 2022 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, Ming Luo, Ph.D Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide. 3. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ 4. Please upload a copy of Figures 1 to 11, to which you refer in your text. If the figure is no longer to be included as part of the submission please remove all reference to it within the text. [Note: HTML markup is below. Please do not edit.] 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: Yes Reviewer #2: Partly ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ****** 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: No ****** 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: No ****** 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: The manuscript by Runke Wang et al., attempt to estimate the near-surface air temperature (Ta) in a complex mountainous area of China by using NDVI, LST, surface albedo, and DEM as the input data and the BP-ANN method. The authors created the Ta dataset with high spatial resolution and investigated its spatial and temporal changes. Moreover, the possible effects of NDVI, LST, and DEM on Ta were also discussed. These findings are of great importance for the regional environmental monitoring in the mountainous area. I would like to recommend an acceptation after these comments as follows are addressed. Major comments: (1) In the Abstract, Lines 28-33: The authors discussed the possible effects of NDVI, LST, and DEM on the air temperature estimation. However, the descriptions over here are not good as the possible mechanisms of the influences of these factors on air temperature are not clearly clarified. Thus, I suggest the authors to rewrite this part to improve the distributions. (2) In the Materials and Methods, Lines 176-179: A total of 14 meteorological stations are used in the study area and the number and the number of stations is small. In this study, the authors divided the 14 stations into two categories. Ten of them were used to drive the model for estimating the near-surface temperature, and the four remaining stations were used to estimate the performance of the model. As the number of the total meteorological stations is small, the above method is not perfect. Thus, I suggest the authors to used ten-fold cross validation method to build the model and then to estimate the performance model. Ten-fold cross validation would perform the fitting procedure a total of ten times, with each fit being performed on a training set consisting of 90% of the total training set selected at random, with the remaining 10% used as a hold out set for validation. If the authors have done the research by ten-fold cross validation method, they can exhibit the new results in comparison with the original results that were obtained based on the previous method. (3) In the results and analysis, it is necessary to perform significance tests for trend analysis as well as correlation analysis. For instance, (1) the significant level of Figure 4b should be given, in which you can exhibit the trend passing 0.05 significant level by dots. In addition, the unit of Figure 4b is not correct. Please check it. In my opinion, "interannual change rate" should be "long-term trend", please check it. (2) In Figure 5, it is necessary to give the p-values for the linear trends as we should know the significant level when we assessing the long-term change. (3) In Figure 6, please give the significant level of long-term trends in air temperatures during four seasons. In addition, please express the related contents in the full manuscript according to atmospheric terminology. (4) In Figure 7, please give the significant level of long-term trend of NDVI. (5) In Figure 8, please give the significant level of correlation coefficient between Ta and NDVI and the region passing the significant test at 0.05 level should be marked by dots. (6) In Figures 9 and 10, please give the significant level and the region passing the significant test at 0.05 level should be marked by dots. Specific comments: (1) The "study area" is found in many places in the abstract, while I cannot find any description of the "study area". It is necessary to give specific information about the study area in the abstract. (2) Line 148: divided -> defined (3) Line 152: Data and processing -> Data (4) Line 153: Remote sensing data and preprocessing -> Remote sensing data (5) Line 160: land cover/land cover -> land use/land cover (6) Line 169: please check the "re obtained" (7) Line 170: Ground data and preprocessing -> Ground data (8) Line 183: Air temperature estimation method -> Air temperature estimation (9) Lines 258-259: The larger the CV, the more obvious the change in NDVI. Please check this sentence carefully. (10) Lines 263-264: There are many grammatical errors in the sentence. Please check it carefully and rewrite this sentence. (11) Line 280: Results and analysis -> Results (12) Lines 282-283: 9580 meteorological stations were selected to establish the equation, while in the data (Figure 1) the number of total meteorological stations is 14. Please it carefully. (13) Line 528: Uncertainty of air temperature estimation results -> Uncertainty of air temperature estimation. (14) Lines 529-531: what does it mean that the RMSE value of all estimated air temperature at the regional scale was still large than the ground observation value? Please check the sentence carefully. (16) Line 538: on time scales of day, month, and year -> on time scales of daily, monthly, and yearly (17) Lines 539-541: For example, studies have shown that ... Please check the sentence carefully. Reviewer #2: The idea and practice of applying (1) remote sensing data like MODIS LST, emissivity, and NDVI, (2) gridded products like land cover and land use, and dem, (3) observation data to build near surface air temperature dataset through the BP-ANN algorithm in Tianshui during 2001~2020. This work lacks scientific merit and the manuscript does not make any significant improvement to the intended field of research. ****** 6. 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 [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. https://doi.org/10.1371/journal.pone.0272946.r001
Revision 1
30 May 2022 Author Response Reviewer #1: The manuscript by Runke Wang et al., attempt to estimate the near-surface air temperature (Ta) in a complex mountainous area of China by using NDVI, LST, surface albedo, and DEM as the input data and the BP-ANN method. The authors created the Ta dataset with high spatial resolution and investigated its spatial and temporal changes. Moreover, the possible effects of NDVI, LST, and DEM on Ta were also discussed. These findings are of great importance for the regional environmental monitoring in the mountainous area. I would like to recommend an acceptation after these comments as follows are addressed. Major comments: (1) In the Abstract, Lines 28-33: The authors discussed the possible effects of NDVI, LST, and DEM on the air temperature estimation. However, the descriptions over here are not good as the possible mechanisms of the influences of these factors on air temperature are not clearly clarified. Thus, I suggest the authors to rewrite this part to improve the distributions. (2) In the Materials and Methods, Lines 176-179: A total of 14 meteorological stations are used in the study area and the number and the number of stations is small. In this study, the authors divided the 14 stations into two categories. Ten of them were used to drive the model for estimating the near-surface temperature, and the four remaining stations were used to estimate the performance of the model. As the number of the total meteorological stations is small, the above method is not perfect. Thus, I suggest the authors to used ten-fold cross validation method to build the model and then to estimate the performance model. Ten-fold cross validation would perform the fitting procedure a total of ten times, with each fit being performed on a training set consisting of 90% of the total training set selected at random, with the remaining 10% used as a hold out set for validation. If the authors have done the research by ten-fold cross validation method, they can exhibit the new results in comparison with the original results that were obtained based on the previous method. (3) In the results and analysis, it is necessary to perform significance tests for trend analysis as well as correlation analysis. For instance, (1) the significant level of Figure 4b should be given, in which you can exhibit the trend passing 0.05 significant level by dots. In addition, the unit of Figure 4b is not correct. Please check it. In my opinion, "interannual change rate" should be "long-term trend", please check it. (2) In Figure 5, it is necessary to give the p-values for the linear trends as we should know the significant level when we assessing the long-term change. (3) In Figure 6, please give the significant level of long-term trends in air temperatures during four seasons. In addition, please express the related contents in the full manuscript according to atmospheric terminology. (4) In Figure 7, please give the significant level of long-term trend of NDVI. (5) In Figure 8, please give the significant level of correlation coefficient between Ta and NDVI and the region passing the significant test at 0.05 level should be marked by dots. (6) In Figures 9 and 10, please give the significant level and the region passing the significant test at 0.05 level should be marked by dots. Specific comments: (1) The "study area" is found in many places in the abstract, while I cannot find any description of the "study area". It is necessary to give specific information about the study area in the abstract. (2) Line 148: divided -> defined (3) Line 152: Data and processing -> Data (4) Line 153: Remote sensing data and preprocessing -> Remote sensing data (5) Line 160: land cover/land cover -> land use/land cover (6) Line 169: please check the "re obtained" (7) Line 170: Ground data and preprocessing -> Ground data (8) Line 183: Air temperature estimation method -> Air temperature estimation (9) Lines 258-259: The larger the CV, the more obvious the change in NDVI. Please check this sentence carefully. (10) Lines 263-264: There are many grammatical errors in the sentence. Please check it carefully and rewrite this sentence. (11) Line 280: Results and analysis -> Results (12) Lines 282-283: 9580 meteorological stations were selected to establish the equation, while in the data (Figure 1) the number of total meteorological stations is 14. Please it carefully. (13) Line 528: Uncertainty of air temperature estimation results -> Uncertainty of air temperature estimation. (14) Lines 529-531: what does it mean that the RMSE value of all estimated air temperature at the regional scale was still large than the ground observation value? Please check the sentence carefully. (16) Line 538: on time scales of day, month, and year -> on time scales of daily, monthly, and yearly (17) Lines 539-541: For example, studies have shown that ... Please check the sentence carefully. Reviewer #2: The idea and practice of applying (1) remote sensing data like MODIS LST, emissivity, and NDVI, (2) gridded products like land cover and land use, and dem, (3) observation data to build near surface air temperature dataset through the BP-ANN algorithm in Tianshui during 2001~2020. This work lacks scientific merit and the manuscript does not make any significant improvement to the intended field of research. Attachments Attachment Submitted filename: Response to Reviewers2-(PONE-D-22-09843).docx https://doi.org/10.1371/journal.pone.0272946.r002
30 Jun 2022 Decision Letter - Ming Luo, Editor PONE-D-22-09843R1Study on air temperature estimation and its influencing factors in a complex mountainous areaPLOS ONE Dear Dr. Wang, 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 Aug 14 2022 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, Ming Luo, Ph.D Academic Editor PLOS ONE [Note: HTML markup is below. Please do not edit.] Reviewers' comments: [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. https://doi.org/10.1371/journal.pone.0272946.r003
Revision 2
3 Jul 2022 Author Response 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. Reply: Thank you very much We have already uploaded the figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, and all the figures have passed the inspection and meet PLOS requirements. Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0272946.r004
1 Aug 2022 Decision Letter - Ming Luo, Editor Study on air temperature estimation and its influencing factors in a complex mountainous area PONE-D-22-09843R2 Dear Dr. Wang, 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, Ming Luo, Ph.D Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0272946.r005
Formally Accepted
5 Aug 2022 Acceptance Letter - Ming Luo, Editor PONE-D-22-09843R2 Study on air temperature estimation and its influencing factors in a complex mountainous area Dear Dr. Wang: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. 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. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Ming Luo Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0272946.r006

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