Extraction of urban built-up area based on the fusion of night-time light data and point of interest data

The accurate extraction of urban built-up areas is an important prerequisite for urban planning and construction. As a kind of data that can represent urban spatial form, night-time light data has been widely used in the extraction of urban built-up areas. As one of the geographic open-source big data, point of interest (POI) data has a high spatial coupling with night-time light data, so researchers are beginning to explore the fusion of the two data in order to achieve more accurate extraction of urban built-up areas. However, the current research methods and theoretical applications of the fusion of POI data and night-time light data are still insufficient compared with the dramatically changing urban built-up areas, which needed to be further supplemented and deepened. This study proposes a new method to fuse POI data and night-time light data. The results before and after data fusion are compared, and the accuracy of urban built-up area extracted by different data and methods is analysed. The results show that the data fusion can avoid the shortage of single data and effectively improve the extraction accuracy of urban built-up areas, which is greatly helpful to supplement the study of data fusion in urban built-up areas, and also can provide decision-making guidance for urban planning and construction.

up areas." Be careful with such strong assertion. The effectiveness of data fusion also heavily and inherently rely on the data quality and fusion methods. Furthermore, you didn't use a method of exhaustion here in your results, so it is better to avoid such assertive and affirmative statements. 18.
Last but not the least, please keep a consistent format for all the entries in the reference list. Please be more rigorous.

Review form: Reviewer 2
Is the manuscript scientifically sound in its present form? No

Comments to the Author(s) See attachement (Appendix A).
Decision letter (RSOS-201268.R0) We hope you are keeping well at this difficult and unusual time. We continue to value your support of the journal in these challenging circumstances. If Royal Society Open Science can assist you at all, please don't hesitate to let us know at the email address below.

Dear Dr He
The Editors assigned to your paper RSOS-201268 "Study on Identification of Urban Built-up Area Based on Nighttime Lighting and POI Data---A Case Study of Kunming, China" have made a decision based on their reading of the paper and any comments received from reviewers.
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Kind regards, Andrew Dunn Royal Society Open Science Editorial Office Royal Society Open Science openscience@royalsociety.org on behalf of Professor Weisi Guo (Associate Editor) and R. Kerry Rowe (Subject Editor) openscience@royalsociety.org Associate Editor Comments to Author (Professor Weisi Guo): Associate Editor: 1 Comments to the Author: Dear authors, I was able to obtain reviews from two expert reviewers. They found that the paper had limited methodological novelty and many issues. However, I also recognise that a lot of good work went into the paper and I do believe there is scope in the future should you wish to seriously improve upon the current version.
Editor Reviewer comments to Author: Reviewer: 1 Comments to the Author(s) This paper is interesting, and the authors conducted a comparison of different data scenarios in terms of identifying urban built-up areas, including nighttime light data, POI data, and a fusion of these two. The Kunming city was used as the case study. The paper has certain merits. However, there are some major concerns associated with the structure, novelty, and conclusions.
1. More up-to-date references can be added to section 2.2 in regards to urban data. For example: ANPR sensor data (Tang, J., Wan, L., Nochta, T., Schooling, J. and Yang, T., 2020. Exploring Resilient Observability in Traffic-Monitoring Sensor Networks: A Study of Spatial-Temporal Vehicle Patterns. ISPRS International Journal of Geo-Information, 9(4), p.247.), Vehicle trajectory data (Liu, J., Han, K., Chen, X.M. and Ong, G.P., 2019. Spatial-temporal inference of urban traffic emissions based on taxi trajectories and multi-source urban data. Transportation Research Part C: Emerging Technologies, 106, pp.145-165.) etc. 2. Section 2.3 -Line 56-60: duplicated content. Please check! 3. Highlighting objectives or main purposes is fine, but please also consider to summarise the key contributions of the paper. 4. Give a reference to "One Belt and One Road". 5. Please further justify "The reason why the research area is not expanded to other districts and counties except the main urban area is mainly due to the significantly lower area of urban builtup areas of other districts and counties than that of the main urban area" why did the authors particularly underscore this point in this section? 6. Figure 2 -it seems that the in-text referencing for figure (a) and (b) in section 3.2.1 -line 55 and section 3.2.2 -Line 2 are mistaken. Should swap the position of (a) and (b) in figure 2. 7. The data sources should be properly cited, not just appending web links in the parentheses 8. Give the full name of all acronyms at their first appearance, such as OSTU, GGM, DN value, etc. 9. All method-related subsections need more details and descriptions. Think about the nontechnical readers. More information and an in-detail and clear description of methods might be helpful. For example, what are the details for the implementations of those methods? 10. Section 4.1.1 -Line 37: Please write "FIG. 3" in a proper style. 11. The authors should use high-resolution figures. 12. Results are a bit too brief. The authors could add more in-depth descriptive discussion to the figures and results. 13. It would be better to use statistical tests to verify the different accuracy and other numerical results for different scenarios. The authors could think of questions like -are the differences in the accuracy statistically significant between pairs of "just POI", "just LJ data", and "combined them together" scenarios? 14. Comment No. 12 could be further tested through adding one or two more case studies of other comparable Chinese cities. Besides, drawing strong conclusions based on just one city case is relatively less convincing. Thus, it is recommended to add more test cases. 15. It would be better to compare your results and findings with one/more previous work(s) which use different data and methods. 16. Discussion is a bit shallow. More deeper thoughts would be useful. For example, what are the benefits for different stakeholders? How is the reliability of the proposed methods? Can this be transferred or have a wider application for other cities, or other areas of research? How would the data quality affect the results and findings? How is the sensitivity of the results (authors could even test the sensitivity in the results), etc. All in all, there are a lot of aspects, useful and insightful aspects, that the authors could expand on, which the authors did not do in the current version. Thus, it is recommended to consider all those points in the revision. 17. In the Conclusion section, the authors claimed that "the study holds the idea that the fusion of data is more important than the selection of methods in the identification of urban built-up areas." Be careful with such strong assertion. The effectiveness of data fusion also heavily and inherently rely on the data quality and fusion methods. Furthermore, you didn't use a method of exhaustion here in your results, so it is better to avoid such assertive and affirmative statements. 18. Last but not the least, please keep a consistent format for all the entries in the reference list. Please be more rigorous.
Reviewer: 2 Comments to the Author(s) See attachement.

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RSOS-210838.R0
Review form: Reviewer 1 Is the manuscript scientifically sound in its present form? Yes

Are the interpretations and conclusions justified by the results? Yes
Is the language acceptable? Yes

Recommendation?
Accept as is

Comments to the Author(s)
Thank you for the revision. The authors did a thorough job on addressing the comments.

Review form: Reviewer 2
Is the manuscript scientifically sound in its present form? No

Do you have any ethical concerns with this paper? No
Have you any concerns about statistical analyses in this paper? No

Recommendation?
Accept with minor revision (please list in comments)

Comments to the Author(s)
Dear authors, I believe the new submission has been improved a lot, but it will still need to be improved to reach the publication standard. See below for detailed comments: 1. P16 L10: please check the reference list accordingly. 2. Figure 1: this gives very limited information. You can actually combine figure 1 and 2 and then make the figure 1 as the inset map. In the figure 2, can you change the legend range from lowhigh to exact light intensity? 3. P18: so why you only have Kunming map but also treat Guangzhou as a study area? 4. Figure 3 is quite confused. Can you combine the 2 flowcharts together and make it clear? 5. Figure 8: this is very hard to see the difference between the 4 figures. Can you make it clear where is the difference? 6.

Decision letter (RSOS-210838.R0)
We hope you are keeping well at this difficult and unusual time. We continue to value your support of the journal in these challenging circumstances. If Royal Society Open Science can assist you at all, please don't hesitate to let us know at the email address below.

Dear Dr He
On behalf of the Editors, we are pleased to inform you that your Manuscript RSOS-210838 "Extraction of Urban Built-up Area Based on the Fusion of Night-time Light Data and POI Data" has been accepted for publication in Royal Society Open Science subject to minor revision in accordance with the referees' reports. Please find the referees' comments along with any feedback from the Editors below my signature.
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Kind regards, Royal Society Open Science Editorial Office Royal Society Open Science openscience@royalsociety.org on behalf of Professor Weisi Guo (Associate Editor) and R. Kerry Rowe (Subject Editor) openscience@royalsociety.org Reviewer comments to Author: Reviewer: 1 Comments to the Author(s) Thank you for the revision. The authors did a thorough job on addressing the comments.
Reviewer: 2 Comments to the Author(s) Dear authors, I believe the new submission has been improved a lot, but it will still need to be improved to reach the publication standard. See below for detailed comments: 1. P16 L10: please check the reference list accordingly. 2. Figure 1: this gives very limited information. You can actually combine figure 1 and 2 and then make the figure 1 as the inset map. In the figure 2, can you change the legend range from lowhigh to exact light intensity? 3. P18: so why you only have Kunming map but also treat Guangzhou as a study area? 4. Figure 3 is quite confused. Can you combine the 2 flowcharts together and make it clear? 5. Figure 8: this is very hard to see the difference between the 4 figures. Can you make it clear where is the difference? 6. Table 2: You should add the equation about how to calculate these measures (recall, precision, F1-score).

===PREPARING YOUR MANUSCRIPT===
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Author's Response to Decision Letter for (RSOS-210838.R0) Decision letter (RSOS-210838.R1) We hope you are keeping well at this difficult and unusual time. We continue to value your support of the journal in these challenging circumstances. If Royal Society Open Science can assist you at all, please don't hesitate to let us know at the email address below.
Dear Dr He, I am pleased to inform you that your manuscript entitled "Extraction of Urban Built-up Area Based on the Fusion of Night-time Light Data and POI Data" is now accepted for publication in Royal Society Open Science.
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Study of Kunming, China
Recommendation: Introduction section is too short and did not really review existing research on urban built-up extraction.

Appendix A
The authors used a lot of acronym in the article but did not really explain it at the first instance.
In terms of data fusion of POI and night lights data, a lot of research have used it before, and I don't think it is a major research barrier anymore.
At the end of the introduction, I don't see a clear explanation in terms of the necessity of this research.  Equations: all the equations should be in a single line rather than embedded in the text.
When you use existing methods such as OSTU, you will need to cite the original reference. Also, it will be good to have a flowchart to explain your methodology.

Point-by-point response to reviewer 1
We would like to extend our sincere thanks to the reviewers who have carefully read our paper and put forward many valuable comments. These comments are believed to have a great effect on the improvement of our paper. In the past few months, we have carefully read every comment and comprehensively revised them according to the full text. No matter whether the final paper is accepted or not, we would like to thank you for your valuable advice. The following specific content is a reply to your comments one by one. Response 1: It has been realized that there are still many key references missing in the study. For this reason, we re-read the relevant research. While reorganizing the literature review, we have added many updated relevant references, which contributes to the increasement to the number of references in the full text from 57 to 72. Reference 15 is added. The detailed information of the reference can be found in the last reference part of the study.
Point 2: Section 2.3 -Line 56-60: duplicated content. Please check! Response 2: We are very sorry that we did not notice this mistake. We have corrected this mistake and checked the full text in detail so that there is no such mistake in the full text.
Point 3: Highlighting objectives or main purposes is fine, but please also consider to summarise the key contributions of the paper.

Appendix B
Response 3: It has been realized that it is not enough to only talk about the goals and objectives of this research and not summarize the main contributions in the last part of the introduction of this paper, so we have reworked this part to further highlight the main contributions. Response 4: Although One Belt and One Road is a well-known initiative in China, as an international paper, we really need to give the reference of this initiative, which will make international readers accept it more quickly. Therefore, we add the following references: Point 5: Please further justify "The reason why the research area is not expanded to other districts and counties except the main urban area is mainly due to the significantly lower area of urban builtup areas of other districts and counties than that of the main urban area" why did the authors particularly underscore this point in this section?
Response 5: In the part of study area, we did not describe the selection of research area enough, which may cause some misunderstanding. Therefore, we made a detailed supplement to this part, and Response 6: This is our mistake that we did not consider the sequence of the pictures when placing them. In order to avoid such a problem, we deleted the original picture and changed the original picture 2 into Figure 2 and Table 1, so that the information of the chart is more readable and the information presented is more complete.
Point 7: The data sources should be properly cited, not just appending web links in the parentheses Response 7: It has been realized that the part of data reference is not standardized enough, and the data link should not be directly placed after it. Therefore, we deleted this part and uploaded all the original data to 10.17605/OSF.IO/C6QUK, so that the use of this data can be directly accessed without reference.
Point 8: Give the full name of all acronyms at their first appearance, such as OSTU, GGM, DN value, etc.
Response 8: There are many abbreviations in the paper, some non-standard abbreviations will cause obstacles to the reading of the paper, so we have standardized and adjusted the abbreviations of the full text, including GGM (green level and gradient mapping), DN (Digital Number), etc., and other abbreviations can be seen in the specific content. As for OSTU, it refers to the whole process of this method, not an abbreviation, so we did not change the abbreviation of it.
Point 9: All method-related subsections need more details and descriptions. Think about the nontechnical readers. More information and an in-detail and clear description of methods might be helpful.
For example, what are the details for the implementations of those methods?
Response 9: Although three methods are mentioned in this paper, the introduction of the method is not very detailed, which will make it difficult for readers who are not are not professional in the field to understand. Therefore, we researched relevant references in this field again and supplemented some details of the method: According to the binarization characteristic (gray characteristic) of the image itself, OSTU algorithm can divide the image into two parts: segmentation scene (foreground) and reference scene The solution steps of Density-Graph are mainly divided into two steps, the first step is to determine the relationship between the density value d and the theoretical radius increment ∧ ( 1 2 ⁄ ), and to obtain the derivative of the theoretical radius increment ∧ ( 1 2 ⁄ ). For the theoretical radius increment ∧ ( 1 2 ⁄ ) is derived, the equation d holds in theory. If the equation is equal to 0, then the density curve is uniformly diffused outwards. However, it is well known that there is basically no uniform expansion mode in urban built-up area expansion. Therefore, if the equation is greater than 0, the density curve is diffused outwards; if the equation is less than 0, the density curve is contracted inwards. The second step is to judge the critical value of density graph calculation. Actually, urban is a very complex system. As most cities are non-uniform outward expansion from multiple city centers or clusters of cities, the Kernel Density Curve of point elements changes dramatically inside the urban space, which is also the reason why the performance of the Density-Graph curve inside the city should be fluctuating. However, from the macro scale of the whole urban space, the fluctuation of the Density-Graph curve should have a critical point with global significance. When confusedly, which caused the reviewer's misunderstanding. I am very sorry for this. Therefore, we have readjusted all the charts in the full text, and unified adjustment has been made to the format and style of reference. The specific content can be seen in the study.
Point 11: The authors should use high-resolution figures.
Response 11: We are very sorry that our low-resolution images do not reflect the detailed information of the paper. In order to solve this problem, we have done two things. First, we have remade all the pictures to ensure that the quality of the pictures is greater than 330dpi, and then we uploaded all the original pictures to the RSOS submission system.
Point 12: Results are a bit too brief. The authors could add more in-depth descriptive discussion to the figures and results.
Response 12: Indeed, our description of the experimental results was a little simple, which prevented us from presenting different data and experimental results expressed in the paper, especially in the part of result verification part. Therefore, we re-compared the experimental results, and the supplementary results are as follows: Accuracy verification is an important step to test the reliability of this method for urban built-up area extraction. In this study, the urban built-up areas of Guangzhou are extracted by the fusion of Guangzhou night-time light data and POI data, besides, the confusion matrix and overall accuracy are used to verify the reliability and practicability of data fusion for the extraction of urban built-up areas.
The extracted urban built-up areas of Guangzhou and the confusion matrix and accuracy verification are shown in Table 3. (Line 329-333) It can be seen from Table 3  in the accuracy statistically significant between pairs of "just POI", "just LJ data", and "combined them together" scenarios?
Response 13: In the part of result verification, we realized that the description was a bit confusing, so we verified the results again and verified the research results in detail by using statistical test. The specific contents are shown in Table 3. It can be seen from Table 3  Other details can be referred in the study.
Point 15: It would be better to compare your results and findings with one/more previous work(s) which use different data and methods.
Response 15: The results of this study need to be compared with others to find the value of this study. Therefore, we sorted out the current international papers on the extraction of urban built-up areas and compared the results of this study with these studies to highlight the value of this study. The specific contents are as follows: On the one hand, compared with other urban built-up area extraction studies, this study proposes a new method based on image recognition (OSTU) to extract urban built-up area with night-time light data. In addition, this study also uses geometric mean to fuse night-time light data and POI data to There is no doubt that the accuracy of the research data will also affect the accuracy of the final urban built-up area extraction. For example, the spatial resolution of Luojia1-01 data is 130M, while other night-time light data such as NPP is 500M, which will have a great impact on the accuracy of urban built-up areas extracted before and after data fusion. Although this problem has not been discussed in this study, it will be the focus of the next studies. (Line 385-393) Point 17: In the Conclusion section, the authors claimed that "the study holds the idea that the fusion of data is more important than the selection of methods in the identification of urban built-up areas." Be careful with such strong assertion. The effectiveness of data fusion also heavily and inherently rely on the data quality and fusion methods. Furthermore, you didn't use a method of exhaustion here in your results, so it is better to avoid such assertive and affirmative statements.
Response 17: It has been realized that there are some problems with the expression of conclusions.
The main reason is that the research we have done is limited to the research of the entire subject, and we cannot draw some conclusions outside of this research subjectively. Therefore, we reorganized this research and re-described the conclusion part based on the research results of this research: In list. Please be more rigorous.
Response 18: As for the references in this study, we found that some references were in different formats, which aroused our attention. Therefore, we rearranged the references, including the newly added ones, to ensure that all references were in uniform citation formats.
Point-by-point response to reviewer 2 We would like to extend our sincere thanks to the reviewers who have carefully read our paper and put forward many valuable comments. These comments are believed to have a great effect on the improvement of our paper. In the past few months, we have carefully read every comment and comprehensively revised them according to the full text. No matter whether the final paper is accepted or not, we would like to thank you for your valuable advice. The following specific content is a reply to your comments one by one. Response 2: We are very sorry that our low-resolution images do not reflect the detailed information of the paper. In order to solve this problem, we have done two things. First, we have remade all the pictures to ensure that the quality of the pictures is greater than 330dpi, and then we uploaded all the original pictures to the RSOS submission system.
Point 3: It looks like the authors use summary instead of abstract, and please read the journal requirement carefully before any submission.
Response 3: At the beginning, we did not understand the difference between Abstract and Summary in the writing of the paper. We wrote Abstract in the first version of the paper. In the process of revision, we compared the RSOS paper and rearranged the summary of this study as follows: Appendix C The accurate extraction of urban built-up areas is an important prerequisite for urban planning and construction. As a kind of data that can represent urban spatial form, night-time light data has been widely used in the extraction of urban built-up areas. As one of the geographic open-source big data, POI (Point of Interest) data has a high spatial coupling with night-time light data, so researchers begin to explore the fusion of the two data in order to achieve more accurate extraction Response 4: It's true that the identification of urban built-up area is not a very difficult problem.
We made too subjective judgment when writing the paper. Therefore, when we reorganized the paper, we deleted all the sentences that are too subjective in the paper, which made the paper look more rigorous. The specific modification content can be viewed in the full text.
Point 5: Introduction section is too short and did not really review existing research on urban built-up extraction.
Response 5: It has been realized that there is no complete review of the research on the extraction of urban built-up areas in the introduction part, which cannot be ignored for the research on urban built-up areas. Therefore, we have re-sorted the research on urban built-up areas, and revised the introduction part as follows: The (Line 51-68) Point 6: The authors used a lot of acronym in the article but did not really explain it at the first instance.
Response 6: There are many abbreviations in the paper, some non-standard abbreviations will cause obstacles to the reading of the paper, so we have standardized and adjusted the abbreviations of the full text, including GGM (green level and gradient mapping), DN (Digital Number), etc., and other abbreviations can be seen in the specific content. As for OSTU, it refers to the whole process of this method, not an abbreviation, so we did not change the abbreviation of it.
Point 7: In terms of data fusion of POI and night lights data, a lot of research have used it before, and I don't think it is a major research barrier anymore.
Response 7: It's true that there are many studies discussing the study of two types of data fusion in urban space, but different studies have different focuses. This study focuses on the advantages of data fusion in the extraction of urban built-up areas, this further complements the research of data fusion in urban area, which is of certain theoretical and practical value.
Point 8: At the end of the introduction, I don't see a clear explanation in terms of the necessity of this research.
Response 8: It is true that in the process of submitting the paper before, we did not clearly explain the necessity of research in the introduction part, so we revised the last part of it, including clearly explaining the purpose, goal and necessity of the research, and the specific modifications are as follows: Therefore, in order to extract the urban built-up area more accurately and supplement the related  Response 10: There are many formulas involved in this study, but the format of several formulas is wrong, so we rechecked all the formulas and re-typeset the content and format of these formulas.
For specific modifications, you can check the parts of each formula. Point 11: When you use existing methods such as OSTU, you will need to cite the original reference. Also, it will be good to have a flowchart to explain your methodology.
Response 11: It has been realized that when quoting documents, it did not take into account that the OSTU method is less involved in previous studies. Then the original document must be found for the quotation of this method, which will make the application of the method more credible, so we In addition, it has been realized that this study is relatively complex on the whole, including various data, methods and verification parts. Therefore, a clear flow chart is needed to clarify this study. Therefore, a new flow chart is added in Figure 4 to make the framework of this study clearer.  [191][192][193][194]