Analysis on the Rationality of Urban Green Space Distribution in Hangzhou City Based on GF-1 Data
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data
2.3. Data Pre-Processing
2.4. Method
3. Results
3.1. Extraction of UGS of Shangcheng District
3.2. Extraction of UGS of the Main Urban Area of Hangzhou
3.2.1. Special Distribution of UGS in Hangzhou
3.2.2. Special Distribution of UGS in Each District
4. Discussion
4.1. Accuracy Analysis
4.1.1. Comparison with Statistical Yearbook
4.1.2. Stability Analysis
4.1.3. Comparison of Different Methods
- 1.
- Normalized Difference Vegetation Index (NDVI) model
- 2.
- Pixel Bipartite Model
4.2. Analysis of Temporal Changes of UGS in Shangcheng District
4.3. Analysis of Spatial Distribution of UGS in the Main Urban Area of Hangzhou
4.3.1. Special Distribution of UGS in the Main Urban Area in Hangzhou
4.3.2. Special Distribution of UGS in Each District
4.4. Analysis of Temporal Changes of UGS in Shangcheng District
4.4.1. Policy
4.4.2. Resident Demand
4.4.3. Economic Development
4.5. Strengths, Limitations, and Future Study
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Sensor | Band Number | Wavelength (μm) | Spatial Resolution (m) | Width (km) | Side Pendulum Angle | Revisit Cycle |
---|---|---|---|---|---|---|
PMS | 1 | 0.45–0.90 | 2 | 60 | ±35° | 4 Days |
2 | 0.45–0.52 | 8 | ||||
3 | 0.52–0.59 | |||||
4 | 0.63–0.69 | |||||
5 | 0.77–0.89 |
NO. | Forest Area (km2) | Grassland Area (km2) | UGS Area (km2) | Percentage of UGS (%) |
---|---|---|---|---|
1 | 6.53 | 2.96 | 9.48 | 36.38 |
2 | 7.78 | 1.80 | 9.58 | 36.76 |
3 | 6.36 | 2.54 | 8.9 | 34.15 |
4 | 6.32 | 2.92 | 9.24 | 35.46 |
5 | 6.12 | 2.37 | 8.49 | 32.58 |
6 | 7.38 | 1.96 | 9.34 | 35.84 |
Forest | Grassland | UGS | ||||
---|---|---|---|---|---|---|
Area (km2) | Percentage (%) | Area (km2) | Percentage (%) | Area (km2) | Percentage (%) | |
2018 | 6.52 | 25.02 | 2.96 | 11.36 | 9.48 | 36.38 |
2020 | 7.93 | 30.43 | 2.41 | 9.25 | 10.34 | 39.68 |
Grade | Forest (km2) | Grassland (km2) | UGS (km2) | Percentage of Forest (%) | Percentage of UGS (%) |
---|---|---|---|---|---|
Very low (0–0.2) | 7.17 | 7.00 | 14.17 | 1.02 | 2.01 |
Low (0.2–0.4) | 25.59 | 18.49 | 44.06 | 3.62 | 6.24 |
Medium (0.4–0.6) | 40.34 | 24.50 | 64.84 | 5.71 | 9.18 |
Medium high (0.6–0.8) | 45.34 | 25.41 | 70.75 | 6.42 | 10.02 |
High (0.8–1) | 100.15 | 56.06 | 156.21 | 14.18 | 22.12 |
Total | 218.59 | 131.46 | 350.05 | 30.95 | 49.56 |
Grade | Xihu | Xiacheng | Shangcheng | Jianggan | Gongshu | Binjiang | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
(km2) | (%) | (km2) | (%) | (km2) | (%) | (km2) | (%) | (km2) | (%) | (km2) | (%) | |
Very low (0–0.2) | 6.01 | 1.94 | 0.64 | 2.18 | 0.46 | 1.77 | 4.13 | 2.07 | 1.64 | 2.37 | 1.30 | 1.80 |
Low (0.2–0.4) | 19.65 | 6.35 | 1.96 | 6.68 | 1.57 | 6.02 | 12.03 | 6.02 | 4.84 | 6.99 | 4.01 | 5.55 |
Medium (0.4–0.6) | 30.21 | 9.76 | 2.56 | 8.73 | 2.27 | 8.71 | 17.33 | 8.67 | 6.78 | 9.79 | 5.68 | 7.86 |
Medium high (0.6–0.8) | 36.54 | 11.81 | 2.20 | 7.50 | 2.21 | 8.48 | 17.46 | 8.73 | 6.98 | 10.08 | 5.36 | 7.42 |
High (0.8–1) | 107.05 | 34.60 | 2.14 | 7.30 | 3.83 | 14.70 | 25.23 | 12.62 | 9.91 | 14.31 | 8.11 | 11.23 |
Total | 199.46 | 64.46 | 9.5 | 32.39 | 10.34 | 39.68 | 76.18 | 38.09 | 30.15 | 43.54 | 24.46 | 33.87 |
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Zhang, D.; Liu, H.; Yu, Z. Analysis on the Rationality of Urban Green Space Distribution in Hangzhou City Based on GF-1 Data. Sustainability 2023, 15, 12027. https://doi.org/10.3390/su151512027
Zhang D, Liu H, Yu Z. Analysis on the Rationality of Urban Green Space Distribution in Hangzhou City Based on GF-1 Data. Sustainability. 2023; 15(15):12027. https://doi.org/10.3390/su151512027
Chicago/Turabian StyleZhang, Danying, Haijian Liu, and Zhifeng Yu. 2023. "Analysis on the Rationality of Urban Green Space Distribution in Hangzhou City Based on GF-1 Data" Sustainability 15, no. 15: 12027. https://doi.org/10.3390/su151512027