Deciphering China’s Socio-Economic Disparities: A Comprehensive Study Using Nighttime Light Data

Round 1

Reviewer 1 Report

This is an interesting and important study. The authors applied geospatial analysis methods to examine spatial and temporal disparities between China’s eastern and western portions demarcated by the Hu Huanyong Line. Furthermore, using innovative nighttime satellite data to examine the clustering patterns of urbanization complements most existing studies that rely on traditional statistics collected by the government. However, I have identified a number of issues that I recommend the authors address to improve the quality of this manuscript.

1. Line 42 in page 1, the phrase of “traditional statistical data” is not clear. Provide some examples.

2. Line 61, GDP needs to be spelled out for the first time of use in this paper.

3. Line 66-69. Explain what nighttime satellite data is about and who collected the data…its spatial and temporal resolution, geographical coverage…

4. Line 86-87, the statement of “the coastal regions of China represent an area that has been somewhat overlooked in research circles” is not correct. Indeed, extensive studies have been conducted in the existing literature with respect to urbanization, FDI, and economic development, etc.

5. A review of the existing studies on spatial disparities in economic development in China is highly recommended in the introduction section.

6. Line 131-134, were the statistics about the territories and populations on each side of the Hu Huanyong Line remaining the same as in the 1930s when Hu first observed this geographic division?

7. Figure 1. The pictures from Wikipedia are not helpful here at all - suggest removing them. Besides, Wikipedia is generally not considered as a solid source for academic research.

8. Section 2.2.1, it is important to depict an assumption that nighttime lighted areas can be used as a proxy for urbanization and economic development. The larger or brighter the lighted area, the more urbanized or more developed. Fortunately, you mentioned this in the caption of Figure 2. But this statement needs to be described in the Methodology section. Citations are necessary because a lot of studies used nighttime satellite data to study urbanization or estimate population density or economic development (e.g., GDP).

9. Table 1 in section 2.3.2 is not necessary to be included in the manuscript.

10. Were urban built-up areas provided by government sources used to verify the accuracy of the satellite-derived data for urban areas? A limitation of using nighttime satellite data to estimate urbanization is that it is sensitive to the threshold used to dichotomize urban and rural areas. This issue should be discussed in the conclusion section as a limitation of this study.

11. Discussions about Spatial-Temporal Economic Center of Gravity in Section 3.3 should be mentioned in the Data and Methods section. Now it looks absurd because you never mentioned this kind of analysis Section 2. What data was used and how was it calculated for each year?

 12. Detailed results reported in the Discussion section should be moved to the Results section.  

Author Response

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Reviewer 2 Report

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Reviewer 3 Report

The paper presents an in-depth analysis of socio-economic development and green space distribution in China from 1992 to 2015, utilizing nighttime light data and the Normalized Difference Vegetation Index (NDVI). The study uncovers significant regional disparities in development, explores the dynamics between human activity and environmental sustainability, and offers insights into the effectiveness of socio-economic policies. The paper tells a story, and it's a compelling one. From the stark contrasts between coastal and western regions to the hopeful signs of narrowing gaps.

The paper's analysis is thorough and well-presented. The longitudinal trends, spatial-temporal dynamics, and the use of Gini coefficients to assess inequality are particularly strong points. The conclusions drawn from the study are not just academic - they have real-world implications. The insights provided could be a valuable resource for policymakers looking to foster sustainable and balanced development in China.

Specific Comments

1         Lines 161-164: The method for categorizing counties based on nighttime lights is interesting but could benefit from further justification or reference to existing methodologies.

2         Lines 256-259: The introduction of spatial-temporal patterns of nighttime lights and green spaces is well-presented. However, the connection between these patterns and broader socio-economic trends could be elaborated further.

3         Lines 292-294: Consider revising the sentence for better flow and coherence and ‘R2’ needs to use superscript or ‘^’.

4         Figure 5, Lines 378-381: The comparison of nighttime light intensities between coastal areas and counties west of the Hu Line is compelling but could benefit from additional context or explanation. How do these findings relate to existing literature or theoretical frameworks?

5         Lines 390-395: The explanation of the Gini coefficient could be rephrased for better understanding by a broader audience.

6         Lines 411-415: The mention of major national initiatives is valuable but might be strengthened by providing more detailed information on how these specific policies have contributed to the observed trends.

7         Lines 504: The statement about coastal development nearing saturation is an important finding but may need more empirical support or references to existing studies.

8         Lines 476-528: The conclusion effectively summarizes the key findings but could further highlight the unique contributions of the study to the existing body of literature.

In conclusion, the paper offers valuable insights into socio-economic development and green space distribution in China, with potential implications for policy and sustainability. The minor revisions suggested aim to clarify certain aspects of the methodology, provide deeper context and interpretation for the findings, and further highlight the unique contributions of the study. this manuscript could be accepted after minor revisions.

The language needs to be minor revision

Author Response

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Reviewer 4 Report

This research paper presents an intriguing and appealing subject for investigating the dynamic shifts and spatial distributions of socio-economic development disparities on both sides of the Hu Line. The study utilizes data on night lights and vegetation indexes. Various quantitative methods, such as Developmental Trends Analysis, spatial autocorrelation analysis, Nightlight-Vegetation Ratio Index, and Gini coefficient, are employed to explore the topic. The overall analysis method is commendable, the content is extensive, and the logical structure is robust. Here, I have some questions and suggestions to offer.

Is it really essential to dedicate such a significant portion of the introduction and data introduction to traditional night light research, which is not a novel approach?

This research comprises several distinct modules, such as index calculation, trend analysis, spatial autocorrelation analysis, and Gini coefficient analysis. What connects these various sub-studies? Is there a central theme that guides and unifies them?

Why is the focus of this study solely on mainland China? Shouldn't spatial autocorrelation analysis be applicable regardless of geographical boundaries, considering its reliance on spatial continuity?

Author Response

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Reviewer 5 Report

The article presents a methodology for studying regional disparities in China using satellite data. Night time light (NTL) data are used in order to measure inequalities in broad regions in China, while vegetation data are used in order to examine whether economic development as expressed by the night light data is resulting to reduced vegetation.

There is a suggestion in the article that NTL data are more accurate in depicting inequalities relative to Census data. However, the population and other characteristics in census data capture many aspects of socioeconomic development and there is a question whether the results of the NTL analysis correspond to this data. Although there is relevant literature, the authors might wish to check their results using census data for one or two of the years in the time period they use.

In terms of the relationship with vegetation, the NLT/NDVI index is used. While a decrease of vegetation due to urbanization is expected, the results show an increase in vegetation in the time period examined, which is a very interesting result.  Furthermore, is the change in vegetation related solely to socioeconomic development as expressed by the NTL data? Probably there are policies for protecting or expanding vegetation.

Although I understand that the main purpose of the article is to use remote sensing techniques, I believe there should be a more in-depth discussion on the above issues.

Some more specific remarks are as follows:

In several figures it seems that in the years 2014 and 2015 the temporal trends are changing. See for example Figures 3, 4 and 6. What happened in these years?

There are some problems with the structure of the article. Table 1 refers to the NTL/NDVI index before its presentation in section 2.3.3. In the same Table the interpretation of both types of outliers needs explanation. Also, sections 4.1 and 4.3 in Discussion present results and methods and they belong to the corresponding sections.

In lines 154-160 the methodology of deriving and verifying NTL data is presented. I think further elaboration is needed here, for example the consistency between observed and synthesized data is examined by the authors or it is based on the literature mentioned?

Lines 294-295: I believe instead of 106 is 1E6

Line 330: What weights are used?

Line 379: Instead of number, is it proportion?

Line 426: How secondary growth areas are defined?

Lines 503-504: Is this conclusion supported for specific buffers?

The figures in Tables A1 and A2 need some explanation. In Table A1 are the numbers some sort of averages for the time period examined? In Table A2 the numbers express a difference between coastal and western NTL measurements?

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Round 2

Reviewer 1 Report

I thank the authors for addressing my comments in the previous round of review. The revised manuscript is very much improved. The only minor suggestion is that when describing regional disparities demarcated by the Hu Line in the introduction section, it is necessary to point out what the regional disparities are across China, especially which side is more developed and more urbanized (obviously the east coastal side) and which side is economically backward. To the authors and Chinese readers, this might be common sense, however, to international readers, this needs to be clarified. 

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Reviewer 2 Report

Thank you for addressing the previous comments. I agree with the revisions made so far, and I believe the manuscript is now suitable for publication. However, I would like to draw your attention to a minor point. The paper lacks comparisons with established baselines in the field, which may limit the clarity of the proposed approach's novelty and contribution. While I don't require further revisions, I suggest considering this aspect for future research or discussions.

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