Classification of Shrinking Cities in China Based on Self-Organizing Feature Map
Round 1
Reviewer 1 Report
The present paper focuses on the shrinking city phenomenon in China. SOFM Neural Network is utilized for the city classification. The study is indulging.
There are extreme language issues in the article. From tense preferences to word choices is very problematic. I did not understand half of what I read. This readability issue must be solved with a professional language service.
In general, the literature investigation must be strengthened. The reasoning of indicator selection is vague, that must be clearer. Also, how the weight of these indicators is calculated should be more elaborated, the current form is not enough informative. The expression of the results should be conducted more wisely, the current text is quite simple.
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
The Article „Classification of Shrinking Cities in China based on Self-Organizing Feature Map” relates to shrinking cities in China. Based on the data of the two population censuses of the 6th and 7th censuses The Authors show that China's shrinking cities can be divided into four categories: (1) High population shortage-Low economic development City; (2) High urban expansion-Low population retention City; (3) Low population loss-High traffic accessibility City and (4) Low environmental quality-High passive siphon City. The population, economy, society, and space indicators are selected to cluster the shrinking cities through SOFM neural network.
The article is an interesting proposal, which is in line with current research trends. It was properly structured, containing all the elements that should be found in a good scientific article.
However, I have a few comments on the content presented:
1 Please provide more justification for the use of SOFM neural network. Do the results obtained, really differ from the analysis based only on demographic indicators, related to population and population density? Would the classification of the analyzed cities based only on demographic data differ from the obtained results?
2. In connection with comment 1 - I miss an analysis indicating whether the data taken for analysis are not correlated with each other. Analyzing the indicators taken for the study there is a great danger of such correlation, and in such a situation an analysis based on demographics alone would prove sufficient... Did the authors check the correlation of indicators? If not, do they not think it is necessary here?
3. The Authors, in the Introduction chapter, point to several studies carried out in China on this topic, as confirmed by the items in the References. Please add in the Discussion chapter, a comparison of the results obtained with other studies conducted by other researchers using other methods. Did the proposed methodology generate different results, or did it only confirm the conclusions of other authors?
4. In the Discussion section, it would also be useful to refer to the results of this type of analysis around the world. As it stands, the article is very local in nature.
5. Figure 4 - why are areas shown and not cities? One gets the impression that the authors analyzed data for areas and not for cities. Please correct the map.
6. Figure 8 b - I do not understand why it is combined with 8a? It contains completely different content. Please make a separate Figure from it and in the article add a section containing a comparative analysis.
7. A minor comment - it would be appropriate to explain the acronym somewhere in the article: PM2.5. It is a well-known designation throughout the world, but in a scientific article it should be explained.
The article needs to be supplemented and improved.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Abstract is too long, and it is not self-explanatory: data about the aims of the paper and the importance/consequences of the main results is missing.
Introduction presents a review of the state of the art that properly identify the main limits of the current research about the shrinking cities in China and in the Western countries. The aim of the paper responds to the identified research gaps.
Material and method
The authors should explain the choice of the categorical indicators (section 2.1.2) in line with the main fundings from the literature review. The limits of the indicators from table 1 are not described.
Results – present in a comprehensive graphical representation valuable finding for the decision makings.
Discussions –the authors pointed some of the reasons that explained the city clusters identify in the paper. Such discussions should be extended to better reveal the factors for shrinking cities in other parts of the world.
Author Response
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Author Response File: 
Author Response.docx
Round 2
Reviewer 1 Report
There is a satisfactory revision in terms of language, content and visualization. Please re-organize the sentence in 11-13 lines which "shrinking cities" is repeating two times. Please use the same citation format for newly added references.
Reviewer 2 Report
Thank you for your comprehensive response to my comments. The Authors took it very seriously. I am satisfied with their answers and their explanations very much. The article has been corrected and completed. I recommend it for publication in its current version.
