Uncovering Static–Dynamic Interaction Patterns Between Commercial and Residential Spaces Within Beijing’s Sixth Ring Road Using POI and Human Mobility Trajectory Data

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The study aims to identify the static and dynamic patterns of interaction between commercial and residential spaces within Beijing's Sixth Ring Road by comparing the spatial distribution of commercial infrastructure with actual movements between residential and commercial areas. The study also seeks to identify key nodes of consumption-related mobility and differences among various categories of commercial services.

The study integrates 340,788 commercial POIs from Amap, 7,691 residential POIs from Anjuke, and Didi OD data. The dynamic analysis is based on trips recorded on January 8, 2025, from which residential-to-commercial movements were identified after data filtering. The methods include kernel density estimation, Average Nearest Neighbor analysis, correlation analysis, and network analysis using out-degree, in-degree, and degree centrality.

The main strength of the study is the integration of static analysis of urban infrastructure with data on actual mobility patterns. The large POI dataset, the classification of commercial facilities into six categories, and the analysis of OD connections at the subdistrict level make it possible to demonstrate that the relationship between residential areas and different commercial functions varies considerably. For example, the correlation with residential areas is substantially higher for living services than for vehicle-related services.

Weaknesses and Directions for Improvement:

1. The dynamic analysis is based on only one day of observations. Paragraph 2.2.2 uses Didi OD data exclusively from January 8, 2025, which limits the temporal representativeness of the findings. It would be preferable to include several days, covering both weekdays and weekends, or to interpret and generalize the identified dynamic patterns more cautiously.
2. It is not sufficiently demonstrated that the selected trips actually represent consumption-related travel. In paragraph 2.2.2, trips occurring between 10:00 and 16:00 from residential areas to commercial areas are interpreted as consumption-related, although the OD data do not directly indicate the purpose of the trip. This classification should be better justified, or a more neutral term such as residential-to-commercial trips should be used.
3. The buffer distances used in paragraph 2.2.2 are insufficiently justified. The selected spatial thresholds directly determine which trips are included in the analysis. The choice of these distances should be explained, and preferably a sensitivity analysis using alternative buffer distances should be conducted.
4. The static and dynamic analyses are not sufficiently integrated. Although static-dynamic interaction is presented as the main contribution of the study, Sections 3.1 and 3.2 largely provide two separate analyses. The authors should directly compare static commercial-residential matching with dynamic OD flows at the same spatial level, for example by identifying areas where static facility provision corresponds to or differs from the actual intensity of travel.
5. Paragraph 2.3.3 should provide a more detailed description of the spatial parameters used in the correlation analysis. The spatial resolution or raster cell size should be clearly specified, and the potential effects of spatial autocorrelation and the scale of analysis on the Pearson correlation coefficients should be discussed.
6. The selection of network indicators in paragraph 2.3.4 requires stronger justification. The analysis is mainly limited to out-degree, in-degree, and degree centrality. The authors should explain why these indicators are sufficient to characterize the network structure or supplement the analysis with other relevant network measures.
7. The datasets refer to different time periods. The commercial POIs are from July 2024, whereas the Didi OD data are from January 2025. Since the study directly compares static and dynamic data, the authors should justify the acceptability of this temporal gap and acknowledge it as a limitation.
8. Some explanations of the findings go beyond the factors directly examined in the study. For example, the distribution of certain commercial services is explained by land costs, parking conditions, and transportation accessibility, although these variables are not directly analyzed. In Sections 3 and 4, the authors should distinguish more clearly between empirically established findings and proposed explanations of the observed patterns.
9. The limitations presented in Section 4 should be expanded. In addition to the acknowledged limitations of ride-hailing data, the authors should address uncertainty regarding trip purposes, dependence of the results on buffer distances, the temporal mismatch between datasets, and the sensitivity of the findings to the selected spatial level of analysis.

 

The study presents an interesting research idea and a strong empirical basis. The most important concerns relate to the dynamic component and the actual integration of the static and dynamic analyses. These include the use of data from only one day, the indirect identification of consumption-related trips, insufficient justification of spatial thresholds, and the lack of a more direct comparison between static and dynamic results. These aspects should be prioritized when revising the manuscript.

Comments on the Quality of English Language

The manuscript would benefit from English language editing. Although the text is generally understandable, there are several grammatical and stylistic issues, including sentence fragments, subject-verb agreement errors, awkward or overly complex sentence structures, occasional punctuation errors, and some unnatural academic phrasing. These issues do not prevent understanding of the study but should be corrected to improve the clarity, precision, and overall readability of the manuscript.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The study addresses an important urban GIScience problem, and it is an integration of commercial POIs, residential POIs, and human mobility data. Overall, this is a good paper, and the authors have appropriately incorporated the datasets, processed the data and conducted the analysis in a scientific manner. The findings are clearly presented. However, discussion and conclusion sections need to be revised. Additionally, some minor issues need to be addressed further to improve the clarity of the manuscript as outlined below.

• In abstract, data processing steps need to be added.
• In Introduction, the authors should clearly mention what is methodologically or conceptually new in the present study compared with the existing studies which are mentioned. Simply combining POI data with Didi OD data is not sufficient to establish strong novelty.
• The study uses only OD data for a single day, January 8, 2025- A single weekday cannot adequately represent temporal variability in urban mobility. Condition/situation like special events, holidays, weekdays/weekends, seasonal differences, and short-term anomalies can substantially alter travel behavior. Therefore, author should add logical explanations of the use of single day data for dynamic analysis.
• conventional Pearson correlation does not adequately account for spatial autocorrelation and spatial dependence, because it is too simplistic for spatial data. Therefore, instead of it, author can use/consider spatial statistical approaches such as Moran's I, bivariate Moran's I, or spatial cross-correlation.
• The classification of network nodes into five tiers needs statistical justification. Otherwise, the resulting five-tier hierarchy may be subjective.
• For spatial data, coordinate system, bandwidth and spatial resolution need to be address
• In Figure 1, it is better to add an inset map of China indicating area of Beijing.
• Data source references need to be added. Like Amap platform
• For all methods used here in this study, please add reference at appropriate location.
• Node centrality assessment method needs to be added in method section.
• The caption of Table 5 is incorrect, please revise it, as it is subdistrict centrality classifications.
• Discussion part needs to be separated from conclusion. Critical discussion is missing and accordingly discussion part needs to be revised.

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Based on multiple sources of data and by employing various quantitative research methods, this study investigates the static–dynamic interaction patterns between commercial and residential spaces within Beijing's Sixth Ring Road. However, the following shortcomings need to be further improved.

1. Add the innovations of this study in both the Abstract and the main text.
2. Suggest adding 1-2 keywords related to specific methods.
3. What theoretical issues does this study aim to address, and what is its value?
4. The paper employs various quantitative analysis methods, such as Kernel Density Estimation, Average Nearest Neighbor Analysis, and Correlation Analysis, but lacks citations to relevant references; it is recommended that these be added.
5. It is suggested that "4. Conclusions and Discussion" be divided into two separate sections. The fourth section is for discussion, and the fifth section is for conclusions. Additionally, the third section is too long; some of the content could be incorporated into the discussion.
6. In the conclusion section, it is recommended to add the limitations of this study and future research ideas.

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have adequately addressed the major concerns raised in the previous review. The revised manuscript is substantially improved, particularly through the use of strength-based network measures, spatial-autocorrelation analysis, buffer-distance sensitivity testing, and direct static-dynamic comparison at the subdistrict level.

A few issues remain:

1. The previous version reported 51,172 selected OD trips, but this number is absent from the revised manuscript. Please report the number of records retained after each main filtering stage and clearly distinguish the number of individual trips from the 8,514 aggregated directed OD links. Please also specify whether the 10:00-16:00 criterion refers to pickup time, drop-off time, or both, and define the criteria used to identify empty-vehicle and incomplete records.
2. Within-subdistrict trips were excluded from both the network and the inbound-mobility indicator used in the static-dynamic comparison. Because such local trips may represent an important component of neighborhood-level commercial-residential interaction, this decision requires further justification. Please report how many trips were excluded and, if possible, compare the results with and without these trips. Otherwise, explicitly acknowledge the potential effect of their exclusion as a limitation.
3. Equation (7) should express the in-strength of node i using flows from node j to node i, for example as ∑ⱼ Pⱼᵢ. The notation in Equations (6)-(8) and their definitions should be made consistent.
4. Since conventional Spearman p-values do not account for spatial dependence, the coefficients should either be treated as descriptive measures of rank correspondence or evaluated using a spatially appropriate significance procedure. A final English-language and formatting revision is also recommended.

Comments on the Quality of English Language

A final English-language and formatting revision is still required. For example, the sentence beginning “Using the kernel density estimation method…” in Section 3.1.1 is a sentence fragment. The final sentence of the Conclusions concerning temporally aligned POIs, multimodal mobility records, and comparisons across spatial units is syntactically unclear and should be reformulated. Minor spacing and reference-formatting inconsistencies, including missing spaces before citations [44] and [46], should also be corrected.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf