Assessing Inequality in Urban Green Spaces with Consideration for Physical Activity Promotion: Utilizing Spatial Analysis Techniques Supported by Multisource Data

Round 1

Reviewer 1 Report

Thank you for the opportunity to read your paper.  The main contribution to research that this paper makes is in the different levels in the size and cost of the UGSs.  I do not agree with the term "quality" however, as it denotes that a UGS is not good.... while you seem to actually mean that it is low cost, which is a much better term. Please think of rephrasing the meaning of LQP. 

Other minor comments are on the attached pdf. 

Comments for author File: Comments.pdf

Author Response

Thank you for your suggestion. After careful consideration, we have redefined the relevant concepts. Firstly, we have introduced the concept of a Supply Adjustment Index (SAI) to measure the internal components of UGS related to promoting physical activities. Following your advice, this index emphasizes the corrective role of UGS supply, rather than implying that UGS with fewer facilities are inferior.

Secondly, based on the proposed SAI, this study categorizes UGS into three types to reflect the level of supply of elements related to physical activities within UGS. (1) Low Supply Park (LSP; q ≤ 0.3): These UGS provide fewer types of services and are mainly used for residents' daily activities nearby. They have advantages such as low construction costs, flexible site selection, and convenient use. (2) Medium Supply Park (MSP; 0.3 < q ≤ 0.6): These green spaces can offer more diverse functions, such as basketball courts, children's play facilities, fitness areas, etc., to meet the needs of different age and interest groups. They have higher construction and maintenance costs and can serve a larger range of resident activities. (3) High Supply Park (HSP; q > 0.6): These green spaces have the richest functions and facilities. In addition to basic leisure functions, they may also include larger-scale activity spaces, such as large sports fields. 

The comments in the PDF file have all been addressed and annotated in the revised manuscript. Some of the modifications are as follows:

(1) The translation at the end of section 2.2.3 has been corrected. “In the street” is a translation error. The intended meaning is “within subdistricts”.

(2) A detailed explanation of the functionality of the Gaode Maps Routing API has been added to section 2.2.4. It is an HTTP-based interface that provides walking, public transit, driving queries, and calculates travel distances. Its advantage lies in providing optional routes and travel times based on real-time traffic conditions, road networks, and modes of travel.

(3) Regarding the description of leisure facilities in the evaluation index of the supply correction index, facilities such as coffee shops and umbrella stands have been included because previous studies have shown that these elements can enhance the attractiveness of UGS, thereby promoting residents' participation in physical activities. We supplemented this explanation in lines 206-211 of the manuscript.

(4) Corrections have been made to the description of the spatial distribution of accessibility for different types of UGS in section 3.1.

(5) Further explanation has been provided in the discussion (section 4.2, lines 501-511) based on your feedback on the results in section 3.2.2.

(6) The format of the table presenting the accessibility test results in section 3.2.2 has been modified. The letters before the housing price levels denote the group numbers. The groups with significant differences and their significance levels are indicated in parentheses after each median.

(7) Additional explanation has been provided in section 2.2.1 regarding the selection of entrances for UGS.

Reviewer 2 Report

Thanks for giving me the chance to review this interesting paper. I have some comments for the authors to improve their manuscript.

1.     First of all, I think you should clearly define and illustrate the concept of spatial inequality before analysis. There are a lot of previous studies for spatial inequality which you may refer to for example:

l  Urban suburbia: Gentrification and spatial inequality in workers' communities in Tokyo, Cities 136, 104247.

2.     Related to the above point, I suggest you to add a diagram of research flow to make your research design clearer.

3.     Overall, your literature review seems insufficient, there are some papers are closely related to your research such as the following. I suggest you to explore some more previous studies and enhance your literature review.

l  Spatial distribution of urban gardens on vacant land and rooftops: A case study of' The Garden City Initiative'in Taipei City, Taiwan, Urban Geography 43 (8), 1150-1175

4.     I suggest you to separate provide a discussion before conclusion section. Please try to compare your results and link your finding with the global findings beyond the local discussion only in Harbin.

Moderate editing of English language required

Author Response

Thank you for your suggestions. In accordance with your feedback, the manuscript has been modified as follows:

Firstly, we have supplemented the literature review, providing further clarification on the concepts of spatial inequality and socio-economic inequality in UGS. Spatial inequality in UGS primarily refers to the mismatch between the distribution of UGS in cities and the population. Previous research conducted in different countries and cities has revealed diverse patterns of spatial inequality and their causes, with contradictions between construction costs and local finances being one of the main reasons for spatial inequality. Unreasonable allocation of UGS may further lead to uneven distribution among different social groups, namely socio-economic inequality in UGS. This study mainly focuses on the inequality of UGS among different income and age groups. The references you provided are very valuable. We have included them in the manuscript and added more references as well. A detailed review is provided in lines 37-65 of the manuscript.

Secondly, a research flowchart has been added before section 2.

Thirdly, the discussion section now includes a comparison with previous studies, further explaining the main findings of this research (see section 4.1 and 4.2 in the manuscript). (1) The results indicate significant differentiation in the types of UGS services available in different areas of the city. We provide a detailed explanation of the differences in UGS services obtained in different areas and possible reasons behind them. (2) Our study, from the perspective of different supply capabilities of UGS, supports the previous viewpoint that decentralized small-scale green interventions are more beneficial for green equity than concentrating on large-scale UGS. (3) We compared with previous research and explained the potential reasons for the inequality of UGS accessibility among different income and age groups. Additionally, we further explained the reasons for UGS inequality from the elements of urban spatial structure.

Finally, we have improved the academic English translation of the article to enhance readability.

Reviewer 3 Report

The manuscript presents a comprehensive examination of urban green space (UGS) inequality, with a focus on the quality of physical activity promotion. It employs advanced spatial analysis techniques and leverages multisource data, addressing a significant issue in urban planning and public health. The authors have made a commendable effort. However, there are several areas that require further attention to strengthen the manuscript.

Materials and Methods:

1.       The manuscript does not provide a detailed account of the sample selection process for UGS. The authors should augment the methodology section with explicit information on the UGS sample selection, such as the total number of UGS within the study's geographical scope, the specific number of UGS examined, and the criteria employed for sample selection.

2.       Please specify if social media data and UAVs imagery were obtained for every UGS within the study. If there are instances where those two items was not obtained, please elaborate on the circumstances and how this may impact the study's conclusions.

3.       The description of road network in section 2.2.4 requires further elaboration. A detailed explanation of the destination entrance selection process is necessary to substantiate the study's claim of methodological advancement over previous research utilizing centroids.

4.       The differentiation among classification of UGS in section 2.3.2 should be articulated with greater precision to avoid potential misunderstandings. The text should emphasize that the three categories of UGS are distinct types designed to meet different application scenarios, rather than implying that high-quality parks are undesirable or less valuable.

5.       The manuscript would benefit from a more exhaustive justification for the choice of the 3SFCA model over other potential spatial accessibility models. While the introduction briefly addresses this decision, a more in-depth discussion is recommended in the Methods section.

Results:

1.       The presentation of UGS classification results in section 3.1 is lacking. The authors should incorporate graphical or tabular representations to effectively illustrate the classification outcomes.

Minor editing of English language required

Author Response

Thank you for your suggestions. We have made the following adjustments to the manuscript:

Firstly, in section 2.2.1, we have provided detailed criteria for selecting UGS and specified the sample size. The UGS in this study meet the following criteria: (1) they have a certain amount of hard area suitable for activities; (2) they have any type of vegetation; (3) they are free and open to the public. A total of 133 UGS suitable for use were identified in the study area, including parks, greenways, and some greened plaza sites.

Secondly, in section 2.2.2, we have explained the acquisition of UGS web photos and high-definition images. For web photos, where there were no sources available, such as corner parks and waterfront green spaces, we supplemented using Baidu Street View maps. For high-definition images, according to the provisions of China's "Interim Regulations on the Management of Unmanned Aerial Vehicle Flights," some residential areas, commercial areas, and industrial land in the main urban area did not obtain flight permits. For UGS in these areas, manual identification and assessment were conducted based on Google satellite images and Street View maps.

Thirdly, in Section 2.2.1, we provided a detailed explanation of the method used for selecting entrances to UGS. High-resolution satellite images of Harbin city were obtained from LocaSpaceViewer (LSV) (using Google Maps 2022 edition) and used as a base map. The entrances of each UGS were manually extracted on the ArcGIS platform. This was done because larger UGS may have multiple entrances, and the distances between these entrances and the centroid can be considerable. This approach improves the accuracy of travel time calculations. For UGS without clearly defined entrances (such as squares), the centroid was used as a representative supply point.

Fourthly, in section 2.3.2, detailed definitions and explanations of UGS types have been provided. We have introduced the concept of a Supply Adjustment Index (SAI) to measure the internal components of UGS related to promoting physical activities. Based on the proposed SAI, this study categorizes UGS into three types to reflect the level of supply of elements related to physical activities within UGS. (1) Low Supply Park (LSP; q ≤ 0.3): These UGS provide fewer types of services and are mainly used for residents' daily activities nearby. They have advantages such as low construction costs, flexible site selection, and convenient use. (2) Medium Supply Park (MSP; 0.3 < q ≤ 0.6): These green spaces can offer more diverse functions, such as basketball courts, children's play facilities, fitness areas, etc., to meet the needs of different age and interest groups. (3) High Supply Park (HSP; q > 0.6): These green spaces have the richest functions and facilities. In addition to basic leisure functions, they may also include larger-scale activity spaces, such as large sports fields. 

Fifthly, in section 2.4, we have provided a detailed description of the model development process. We have developed an Supply-Demand improved 2SFCA (SD2SFCA) model considering the physical activity promotion function of UGS, which improves the traditional 2SFCA model from three aspects: supply, demand, and travel time.

Finally, in section 3.1, we have explained the classification of UGS. Overall, UGS distribution is dense in the western part of the city, with a variety of types, while UGS in the south and east are relatively sparse. MSPs are the most numerous, accounting for 48.87% of the total, concentrated in the northeast. LSP has the fewest numbers, accounting for 24.06%, mostly distributed in the west and central areas. HSP is concentrated in the west, followed by the southeast.

Round 2

Reviewer 2 Report

Thanks for the authors for their efforts on the revision.

I have confirmed all the revisions and considered that the manuscript is acceptable now.

 Minor editing of English language might be appreciated.