Spatio-Temporal Correlation and Optimization of Urban Development Characteristics and Carbon Balance in Counties: A Case Study of the Anhui Province, China
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe paper contributes to study the relationship between urban development patterns and carbon balance. It concerned Anhui Province, China. From the perspective of transforming cities towards sustainable and carbon-neutral entities by 2050 and to contribute to the various underlining initiatives, the paper brings very important contribution.
The global paper structure needs to be readapted to fit with paper presentation standards : Abstract, Introduction, Material and Methods, Results, Discussion and Conclusion.
The context of the paper is well written even if it may be improved from various perspective: i-bringing other global perspectives of the paper, ii-clarification (Ex. L48-49. Are the numbers global or related to Chinese context?), or iii- from correction (Ex. L79-83 correction of GHG balance calculation methods and other appropriate related literature)
For the used Data, within Table 1., 105 Is the total population size (all the counties of the province) or it is only a sample/subset of the population?
The paper is based on various data sources at county level and it integrates both temporal and spatial dimensions and relay on the use of various methods for spatiotemporal analysis such as : i-identifying and calculating landscape level metrics that characterize urban development, ii- LISA Spatiotemporal transition analysis , iii- correlation analysis using GTWR and Geodtector, and vi-K-means counties clustering.
If the methods are well suited for the purpose of the study, some question may rise with the need of further clarification such as :
- a global overview of the methodology (if it is graphical it will be well suited, otherwise sentence based could clarify the linkage between the components of the used methods)
- How data have been aggregated at county level (from various sources at various spatial resolution to a single value at county level) ?
- Tools that have been used for analysis (Spatial Data, LISA, GTWR, Geodtector…) ;
- Geodetector vs KMeans and the temporal dimension is there any ways of improving the analysis towards precluding past factors for the current clusters?
The Results are well described and try to be associated to policy implications. Some general comments could be established :
- Maps and figure needs improvement and further enhancement
- L349. balan vs. balance
- Figures 4-5. You need to use the same symbol levels in order to have clear reading (the presentation thresholds must not be changed from map to map);
- There is no Figure 6-a, 6-b, 6-c (L466, L479, L493…). Figure 7 (L544) have to be replaced by Figure 6.
- Numbers on Figure 7 are not clear.
- Talking about significant statistical relation or weak relation have to relay on hypothesis testing or using well defined statistical analysis method according to a p-value signification level
- Section 3.5.1. (L597-659 and then to 706). I think that this section is not well linked with the previous analysis. It may stress out some linkage of the identified clusters with temporal evolution of urban dynamics metrics and other precluding factors. Having this analysis perspective may facilitate establishment of evolution scenarios that could be used to address and to clarify the best urban lands management strategy that leads to the perspective of cities’ carbon neutrality.
The conclusion and discussion.
It Remains a god synthesis with good element of discussion. I suggest to restructure this section to address : i-discussion from the various perspectives (methodology, data, other factors that are not considered within the scope of the paper such as industrial activities, transportation, … and results and their plausibility regarding various similar works) and then ii-conclusion which conclude and not synthetize the paper results.
Finally, I would felicitate the authors for their contribution and efforts that offers a valuable starting point for understanding the linkage between urban development and carbon balance in Anhui Province.
Author Response
Editors and Reviewers:
Hello!
Thank you very much for all the experts and teachers' valuable opinions on Spatio-Temporal Correlation and Optimization of Urban Development Characteristics and Carbon Balance in Counties: A Case Study of the Anhui Province, China. In view of relevant suggestions, the paper team has made more detailed revisions to the paper on the basis of careful understanding, discussion and analysis, and the revised part is marked in red.Please see the attachment.
Author Response File: 
Author Response.docx
Reviewer 2 Report
Comments and Suggestions for AuthorsThe manuscript is well-written, but I have a few minor points:
The abstract is too long; try to minimize it.
What is the GWTR model? You've used abbreviations without providing their full definitions.
The subheading of the introduction is missing.
Is it necessary to write 'Research Methods'? I think simply 'Methods' is enough.
Equations should be centered.
Line 239: Please use the full words of GWTR as introduced the first time.
The resolution of the figures should be improved."
Author Response
Editors and Reviewers:
Hello!
Thank you very much for all the experts and teachers' valuable opinions on Spatio-Temporal Correlation and Optimization of Urban Development Characteristics and Carbon Balance in Counties: A Case Study of the Anhui Province, China. In view of relevant suggestions, the paper team has made more detailed revisions to the paper on the basis of careful understanding, discussion and analysis, and the revised part is marked in red.Please see the attachment.
Author Response File: Author Response.docx
Reviewer 3 Report
Comments and Suggestions for AuthorsThe paper addresses a relevant topic for contemporary planning challenges by exploring the relationship between urban development and carbon balance. It is well structured and the results are properly discussed. Here below there are some suggestions to be considered before its publication:
- The abstract, in its current configuration, is too long and unable to capture the reader's interest. The focus on results is too strong. I suggest authors to shorten the results description and to re-write the abstract by firstly framing the paper into its reference research context and then clearly stating the research's objective and its possible contribution to a broader scientific audience.
- Section 1 has no title.
- In Section 1, it would be interesting to expand the description of the Chinese plan toward reducing carbon emissions and to understand which are the other key components for achieving "dual carbon" goals.
- The "Research Methods" section would benefit from providing an overview of the whole methodological approach (it would be appropriate to provide a figure to "summarize" the implemented methodological approach), thus allowing reader to better contextualize the different methodological steps in the process within the broader research design.
- In Section 2.1.1. Indicators Selection, it is not clear how the six indicators have been defined.
- Policy recommendations could be included in the Conclusion and Discussion section.
Comments on the Quality of English LanguageThere are some minor mistakes and repetitions in the text (e.g., in lines 122-124 the same sentence is repeated twice).
Author Response
Editors and Reviewers:
Hello!
Thank you very much for all the experts and teachers' valuable opinions on Spatio-Temporal Correlation and Optimization of Urban Development Characteristics and Carbon Balance in Counties: A Case Study of the Anhui Province, China. In view of relevant suggestions, the paper team has made more detailed revisions to the paper on the basis of careful understanding, discussion and analysis, and the revised part is marked in red.Please see the attachment.
Author Response File: Author Response.docx
