Ecological Network Optimization in Urban Central District Based on Complex Network Theory: A Case Study with the Urban Central District of Harbin
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources
2.3. Methods
2.3.1. Landscape Pattern Analysis
2.3.2. Extraction of Ecological Network
2.3.3. Optimization of Ecological Network
2.3.4. Optimization Effect Test of Ecological Network
3. Results and Discussion
3.1. Analysis of Landscape Pattern of Ecological Patches in the Study Area
3.2. Construction of Ecological Network in the Study Area
3.2.1. Identification of Ecological Sourcess
3.2.2. Extraction of Ecological Corridors
3.3. Robustness Analysis of Ecological Network before and after Optimization
3.3.1. Robustness Analysis of Ecological Network before Optimization
3.3.2. Robustness Analysis of Ecological Network after Optimization
3.4. LDF-Based Ecological Network Optimization in the Study Area
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Primary Factor | Secondary Factor | Grade | Ecological Resistance |
---|---|---|---|
Land cover | Land use type | Urban land, rural settlement, other construction land | 9 |
Beach, saline-alkali land, bare land | 7 | ||
Paddy field, dry land, | 5 | ||
Sparse forest, other woodland, canal, medium coverage grassland, marsh | 3 | ||
Forestland, high coverage grassland, lake, reservoir, bush, | 1 | ||
Terrain factor | DEM | 0–1000 m | 9 |
1000–1300 m | 7 | ||
1300–1500 m | 5 | ||
1500–1700 m | 3 | ||
>1700 m | 1 | ||
SLOPE | 0–3 | 9 | |
3–9 | 7 | ||
9–18 | 5 | ||
18–27 | 3 | ||
>27 | 1 | ||
Hydrological factor | MNDWI | <0 | 9 |
0–0.22 | 7 | ||
0.22–0.6 | 5 | ||
0.6–0.8 | 3 | ||
>0.8 | 1 | ||
Vegetation cover | NDVI | <0 | 9 |
0–0.2 | 7 | ||
0.2–0.33 | 5 | ||
0.33–0.6 | 3 | ||
>0.6 | 1 | ||
Traffic factor | Road network density | >1.25 | 9 |
0.85–1.25 | 7 | ||
0.52–0.85 | 5 | ||
0.20–0.52 | 3 | ||
0–0.20 | 1 |
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District | NP (Pieces) | CA (ha) | PLAND (%) | LPI (%) | LSI (%) | COHESION (%) |
---|---|---|---|---|---|---|
Daoli | 19 | 6951.51 | 15.6621 | 8.2965 | 8.2608 | 99.3281 |
Daowai | 12 | 10,946.16 | 17.7908 | 15.9749 | 4.4814 | 99.6878 |
Xiangfang | 11 | 798.30 | 2.3375 | 1.2647 | 4.9206 | 97.3614 |
Nangang | 6 | 222.48 | 1.3211 | 0.9214 | 2.9100 | 95.9299 |
Pingfang | 5 | 269.10 | 2.9136 | 1.1518 | 6.1091 | 96.7406 |
Songbei | 49 | 16,097.40 | 21.8475 | 14.6009 | 13.8865 | 99.5820 |
Hulan | 20 | 13,858.92 | 14.5701 | 13.7796 | 5.5669 | 99.7068 |
Acheng | 76 | 15,855.84 | 18.7051 | 16.8907 | 14.2214 | 99.7605 |
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Song, S.; Xu, D.; Hu, S.; Shi, M. Ecological Network Optimization in Urban Central District Based on Complex Network Theory: A Case Study with the Urban Central District of Harbin. Int. J. Environ. Res. Public Health 2021, 18, 1427. https://doi.org/10.3390/ijerph18041427
Song S, Xu D, Hu S, Shi M. Ecological Network Optimization in Urban Central District Based on Complex Network Theory: A Case Study with the Urban Central District of Harbin. International Journal of Environmental Research and Public Health. 2021; 18(4):1427. https://doi.org/10.3390/ijerph18041427
Chicago/Turabian StyleSong, Shuang, Dawei Xu, Shanshan Hu, and Mengxi Shi. 2021. "Ecological Network Optimization in Urban Central District Based on Complex Network Theory: A Case Study with the Urban Central District of Harbin" International Journal of Environmental Research and Public Health 18, no. 4: 1427. https://doi.org/10.3390/ijerph18041427