Optimization of Green Space Planning to Improve Ecosystem Services Efficiency: The Case of Chongqing Urban Areas
Abstract
:1. Introduction
- What are the characteristics of the landscape pattern of UGS, and does the current UGS structure need to be optimized?
- Are there enough available spaces to cover future demand for UGS development and promote healthy and sustainable development of ES, if current UGS cannot satisfy future demand for ES?
- How can we identify potential areas for creating more UGS and forming an effective UGS planning to optimize UGS structure and promote ES in Chongqing urban areas?
2. Materials and Methods
2.1. Overview of the Research Area
2.2. Research Framework and Data
2.3. Potential Analysis of UGS
2.3.1. Evaluation of Current UGS Status
2.3.2. Adaptability Evaluation and Buffer Analysis
2.3.3. Drawing Map of Potential Areas for UGS Expansion
3. Results
3.1. Evaluation Results of the Current UGS
3.1.1. UGS Size
3.1.2. UGS Form
3.1.3. UGS Structure
3.2. Landscape Pattern Characteristics of UGS and Optimization Methods
- (1)
- The UGS size is relatively reasonable; as the dominant landscape type, regional recreational green spaces provide many necessary ES for the city; and scarcity of urban parks and other green spaces (affiliated green spaces) generates pressing demand among residents for better recreation services.
- (2)
- The UGS form is complex, while the fragmentation of urban parks and other green spaces is relatively high.
- (3)
- In terms of UGS spatial structure in Chongqing, it is characterized by unbalanced spatial distribution, low landscape heterogeneity and connectivity, and remarkable ecological functions of regional recreational green spaces and protected areas.
3.3. UGS Adaptability Evaluation and Buffer Analysis
3.3.1. Identification of Potential Areas for UGS Expansion and Adaptability Evaluation Results
- (1)
- there existed 372 potential patchesin total after searching and vectorizing six types of UGS potential expansion areas (i.e., the six adaptive variables in Table 2) one by one,
- (2)
- each patch’s potential to transform into UGS was assessed by adaptive variables and weight tables and the cumulative weight of each potential patch was calculated; the highest value was 0.4639, the lowest 0.0248, and the average value 0.1789,
- (3)
- the potential map after UGS adaptability evaluation (Figure 4) was designed after standardizing the identified potential patches, which were represented with different colours depending on their respective degree of potential (areas of high, medium, and low potential were standardized to 30, 20 and 10, respectively).
3.3.2. Results of the Analysis of UGS Buffer Zones
3.3.3. Plotting of UGS Comprehensive Potential Map and Effective Planning Map
4. Discussion
4.1. Three Key Problems Regarding the Improvement of ES Efficiency
- The UGS sizes are basically reasonable, but the structure ought to be optimized. As shown in Table 3, (i) urban forests, wilderness, and other green spaces covered by large areas of green vegetation are enormous in size, thus providing a variety of ES for urban areas, (ii) there is a scarcity in urban parks; as they are closely related to residents’ daily activities, this limits the range of recreation services for urban residents, (iii) the fragmentation of UGS is relatively high; combined with the limited connectivity between and accessibility of green patches, they hinder ecological processes and adversely impact the ES efficiency.
- There are enough areas that can be used to optimize the UGS landscape pattern and improve the efficiency of ES. We provided a total of 372 potential patches to accommodate UGS and displayed the potential areas in the final potential areas map after adaptability evaluation and the assignment of cumulative weights to each potential patch.
- Planning optimization and the identification of potential areas to accommodate UGS were conducted by means of the adaptability evaluation of related factors and the buffer analysis regarding the main roads, rivers, and current UGS (Section 2.3.2).
4.2. Structural Characteristics of UGS in Mountainous Areas
4.3. UGS Optimization Strategies for Improving the Efficiency of ES
4.3.1. Protecting the Pivotal Functional Spaces in Combination with Environmental Conditions
4.3.2. Optimizing the Green Space Network through Corridor Connection
4.3.3. Acknowledging the Role and Importance of Ecological Processes to Optimize the Green Space Planning
4.3.4. Appreciating the Composite Functions of Urban Areas to Improve the Resilience of the Urban Ecosystem
4.4. Research Limitations and Future Research
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
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Categories | Types | Periods | Applications |
---|---|---|---|
Vector data 1 | Urban green spaces | 2019 | status evaluation, buffer analysis |
Urban road system | 2019 | buffer analysis, adaptability assessment | |
Urban water system | 2019 | ||
Planning data 2 | Territorial spatial planning Chongqing municipality | 2021–2035 | UGS amendment, potential areas identification of UGS |
Chongqing overall urban planning | 2007–2020 | ||
Chongqing land use overall planning | 2006–2020 | ||
Chongqing beautiful landscape city planning | 2015 | ||
Regulatory detailed planning of Chongqing urban areas | 2006–2020 | ||
Survey data 3 | Suitability variables and weight values | - | adaptability assessment |
Variables | Existing UGS | Wetlands | River Banks | Open Areas or Free Lands | Traffic and Infrastructure Corridors | Demand Areas |
---|---|---|---|---|---|---|
Weights | 0.0393 | 0.4669 | 0.2545 | 0.1405 | 0.0741 | 0.0248 |
Landscape Pattern | Indexes | Regional Recreational Green Spaces | Urban Parks | Ecological Conservation Green Spaces | Other Green Spaces | Summation |
---|---|---|---|---|---|---|
Size | Number of Patches (NP) | 30 | 518 | 5 | 384 | 937 |
Class Area (CA)/ha | 192,888.93 | 5321.00 | 10,082.96 | 721.84 | 20,9014.73 | |
Percent of Landscape (PLAND)/% | 92.28 | 2.55 | 4.82 | 0.35 | 100 | |
Largest Patch Index (LPI)/% | 27.98 | 0.44 | 2.32 | 0.02 | - | |
composition | Patch Density (PD)#/km2 | 0.02 | 9.74 | 0.05 | 53.19 | - |
Mean Patch Size (MPS)/ha | 6884.08 | 27.52 | 2496.49 | 13.14 | - | |
Mean Shape Index (MSI) | 9.65 | 24.16 | 3.39 | 26.59 | - | |
Mean Patch Fractal Dimension (MPFD) | 1.21 | 1.36 | 1.13 | 1.42 | - | |
Structure | Shannon’s Diversity Index (SHDI) | 0.11 | 0.33 | 0.03 | 0.37 | - |
Dominance Index (LDI) | 1.84 | 1.62 | 1.92 | 1.58 | - | |
Connectance Index (CONNECT) | 2.38 | 1.11 | 16.67 | 1.52 | - |
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Yan, S.; Tang, J. Optimization of Green Space Planning to Improve Ecosystem Services Efficiency: The Case of Chongqing Urban Areas. Int. J. Environ. Res. Public Health 2021, 18, 8441. https://doi.org/10.3390/ijerph18168441
Yan S, Tang J. Optimization of Green Space Planning to Improve Ecosystem Services Efficiency: The Case of Chongqing Urban Areas. International Journal of Environmental Research and Public Health. 2021; 18(16):8441. https://doi.org/10.3390/ijerph18168441
Chicago/Turabian StyleYan, Shuiyu, and Jun Tang. 2021. "Optimization of Green Space Planning to Improve Ecosystem Services Efficiency: The Case of Chongqing Urban Areas" International Journal of Environmental Research and Public Health 18, no. 16: 8441. https://doi.org/10.3390/ijerph18168441
APA StyleYan, S., & Tang, J. (2021). Optimization of Green Space Planning to Improve Ecosystem Services Efficiency: The Case of Chongqing Urban Areas. International Journal of Environmental Research and Public Health, 18(16), 8441. https://doi.org/10.3390/ijerph18168441