Connective Urban Greenway Route Planning: A Spatial Optimization Perspective

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Overall, this paper presents an interesting study about choosing the optimal route for an urban greenway in Lhasa, China. The models look solid. The results appear reasonable. But there exist a few issues or concerns in the existing paper.

1.     It lacks a more concrete description of urban greenway, particularly in Lhasa. The introduction section only offers an abstract description without many useful details. How does an urban greenway look like? What elements are needed? What is special about urban greenways in Lhasa, given its elevation and climate? It’d be better to have a figure for illustration. It is not just for improving the readability. The model also needs technical details to select candidates. I did not find how the candidate road segments were selected as no criteria were listed. Does a greenway have to be built along existing roads?

2.     “The urban greenway should be linear shaped without loops, breaks, or intersections.” Where does this definition come from? Why can’t greenways intersect with each other?

3.     Can your model handle more than one greenway at a time? Why and why not?

4.     Are there theories or practical rules of thumb to suggest the range of coverage distance as well as D? The tests with multiple numbers seem arbitrary without explanations.

5.     All three models described in section 3 are quite meaningful. But they all seem to treat individual facilities the same way. Is it possible to assign various weights to facilities according to their importance, capacity, or functionality?

6.     Are POIs the same as facilities in this paper? I was confused while reading it.

7.     Some minor issues such as typos and citations that cannot be found.

Author Response

Please find our item-by-item response in the attached file.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The paper presents a spatial optimization model for planning urban greenway routes, emphasizing their role in connecting various urban facilities such as parks, tourist attractions, and transport hubs. The model aims to balance two objectives: maximizing the number of connected facilities and ensuring access to greenways for the largest possible number of residents. The authors introduce three optimization approaches based on Mixed Integer Linear Programming (MILP), which are tested using the example of Lhasa, China. The main strengths of the study include the innovative application of MILP to urban greenway planning and a detailed empirical study.

The work presents an innovative approach to greenway planning through spatial optimization and the integration of urban infrastructure connectivity, making a significant contribution to the field. The methodology is precise, and the structure is logical. The introduction of different scenarios (single- and multi-objective models) enhances the flexibility and applicability of the model.

However, there are several areas for improvement that would significantly enhance the scientific value of the article. These are outlined and justified in the following points.

1. It would be beneficial to clearly indicate the specific gaps in existing approaches to greenway planning that the article aims to fill. Is it increasing precision in route planning? Or perhaps more efficient connections between facilities in urban space? Although the article introduces a new optimization approach, it would be valuable to more explicitly what exactly makes this solution innovative compared to previous methods and why it is more effective.
2. The goal of the study is not formulated generally, which may hinder a full understanding of the author's intentions and the applications of their model. Although the authors declare that the goal is to optimize greenway routes in the city to connect various facilities and maximize access for residents, there is no reference to why the proposed solutions are better than existing methods. The authors should directly specify what research problem their models solve and what the specific objectives are, for example, "The goal of this study is to develop an optimization model for urban greenway routes that enables more effective connections of existing urban facilities while simultaneously maximizing the number of users of these routes, which has not been sufficiently addressed in previous studies."
3. The lack of a clearly formulated research hypothesis weakens the structure of the study. Formulating a hypothesis that explains which aspects of greenway planning are to be improved by the proposed models would make the study more coherent and focused. A sample hypothesis could be: "The proposed spatial optimization models (MILP) will enable more efficient connections of existing urban facilities and maximize the number of residents with access to greenways, compared to traditional methods based on GIS analysis." The authors should clearly indicate in their hypothesis why the selected models (MCLP-Line-MF, MCLP-Line-ALL, MCLP-Line-MD) are better than other approaches and how they will prove this. For example, they could hypothesize that each of the models optimizes different aspects of route planning (number of facilities, minimal route length, minimal distance from facilities) more effectively than existing methods.
4. The research methods used are largely appropriate to the study's objective, which is to optimize the planning of urban greenway routes. The authors used Mixed Integer Linear Programming (MILP), which is a suitable approach for solving spatial optimization problems in urban environments where the connection of multiple facilities with various constraints (e.g., route length, number of connected facilities) is required.

In this regard, I have two recommendations that would increase the methodological rigor of the article:

To better highlight the advantages of the proposed approach, it is recommended that the results of the MILP model be compared with other commonly used greenway planning methods, such as GIS network analysis (e.g., shortest path, minimal cost distance) or traditional methods based on expert analysis. Such a comparison would help assess whether the proposed models are indeed more effective in solving spatial problems in different urban conditions. Furthermore, it would show in which contexts the MILP model is more useful than other methods.

Conduct a sensitivity analysis examining how changes in key input data (e.g., population size, facility distribution, route length) affect the model's results. This analysis should cover different scenarios and spatial data to assess the model's stability in the face of data changes. Such an analysis would provide a better understanding of the model's resilience to various planning conditions and help urban planners adjust model parameters to the specific needs of different cities. This would make the results more useful and applicable in practice.

5. The discussion of the results should more directly relate to previous research and clearly show how the new method fills the research gap identified earlier (in the Introduction). The discussion of results should include a more detailed comparison of the obtained results with those from other studies. The authors could compare how much more effective their model is in optimizing route length, the number of connected facilities, or minimizing construction costs compared to other methods.

The research gap should be better defined, and how the proposed model addresses it should be explained. For example, the authors could emphasize that existing greenway planning methods do not simultaneously optimize facility connections and maximize resident accessibility, while their model successfully combines both aspects.

 

Improving these elements would enhance the scientific value of the article and its contribution to research on urban greenway planning and spatial optimization.

Author Response

Please find our item-by-item response in the attached file.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have addressed most of my comments. Please consider adding how the model can potentially handle greenways with loops, breaks, intersections in future work.

Author Response

Comment 1: Please consider adding how the model can potentially handle greenways with loops, breaks, intersections in future work.

Response 1: We have added to the conclusion section another possibile research dierction for future research: "Furthermore, the MCLP-Line models assume greenways are linear without loops, breaks, or intersections. Additional constraints might be applied to conditionally allow more complicated shapes while necessary might also be an interesting direction for future research."