Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing
Abstract
:1. Introduction
2. Data and Methods
2.1. Data Sources and Development of UGS Data
2.1.1. Data Sources
2.1.2. Development of UGS Data
2.1.3. Accuracy Assessment
2.2. Analysis Methods
2.2.1. Analysis of UGS Patterns
2.2.2. Analysis of Urban Greening Effectiveness
3. Results and Analysis
3.1. UGS Changes in China’s 70 Cities in 2000–2018
3.2. Regional Divergence of UGS Growth
3.3. Improvements in Urban Greening in Newly Expanded Areas in Cities
4. Discussion
4.1. Satellite Remote Sensing Plays a Pivotal Role in Monitoring UGS Change
4.2. The Massive Effectiveness of City Greening Since the Beginning of the 21st Century in China
4.3. Enhancing Urban Ecosystem Services Induced by Urban Green
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Bader, D.A.; Blake, R.; Grimm, A.; Hamdi, R.Q.; Kim, Y.; Horton, R.; Rosenzweig, C.; Alverson, K.; Gaffin, S.; Crane, S. Urban climate science. In Climate Change and Cities: Second Assessment Report of the Urban Climate Change Research Network (ARC3.2); Cambridge University Press: Cambridge, UK, 2018; pp. 27–60. [Google Scholar]
- Kabisch, N.; Strohbach, M.; Haase, D.; Kronenberge, J. Urban green space availability in European cities. Ecol. Indic. 2016, 70, 586–596. [Google Scholar] [CrossRef]
- Grimm, N.B.; Faeth, S.H.; Golubiewski, N.E.; Redman, C.L.; Wu, J.; Bai, X.; Briggs, J.M. Global change and the ecology of cities. Science 2008, 319, 756–760. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sanchez-Rodriguez, S.; Urge-Vorsatz, D.; Barau, A.S. Sustainable development goals and climate change adaptation in cities. Nat. Clim. Chang. 2018, 8, 181–183. [Google Scholar] [CrossRef]
- Georgescu, M.; Morefield, P.E.; Bierwagen, B.G.; Weaver, C.P. Urban adaptation can roll back warming of emerging megapolitan regions. Proc. Natl. Acad. Sci. USA 2014, 111, 2909–2914. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhu, P.; Zhang, Y. Demand for urban forests in United States cities. Landsc. Urban Plan. 2008, 84, 293–300. [Google Scholar] [CrossRef]
- Sun, C.G.; Lin, T.; Zhao, Q.J.; Li, X.H.; Ye, H.; Zhang, G.Q.; Liu, X.F.; Zhao, Y. Spatial pattern of urban green spaces in a long-term compact urbanization process—A case study in China. Ecol. Indic. 2019, 96, 111–119. [Google Scholar] [CrossRef]
- Bierwagen, B.G.; Theobald, D.M.; Pyke, C.R.; Choate, A.; Groth, P.; Thomas, J.V.; Morefield, P. National housing and impervious surface scenarios for integrated climate impact assessments. Proc. Natl. Acad. Sci. USA 2010, 107, 20887–20892. [Google Scholar] [CrossRef] [Green Version]
- Matos, P.; Vieira, J.; Rocha, B.; Branquinho, C.; Pinho, P. Modeling the provision of air-quality regulation ecosystem service provided by urban green spaces using lichens as ecological indicators. Sci. Total Environ. 2019, 665, 521–530. [Google Scholar] [CrossRef] [PubMed]
- Selmi, W.; Weber, C.; Riviere, E.; Blond, N.; Mehdi, L.; Nowak, D. Air pollution removal by trees in public green spaces in Strasbourg city, France. Urban Urban Gree. 2016, 17, 192–201. [Google Scholar] [CrossRef] [Green Version]
- Nowak, D.J.; Greenfield, E.J. Tree and impervious cover in the United States. Landsc. Urban Plan. 2012, 107, 21–30. [Google Scholar] [CrossRef] [Green Version]
- Byomkesh, T.; Nakagoshi, N.; Dewan, A.M. Urbanization and green space dynamics in Greater Dhaka, Bangladesh. Landsc. Ecol. Enfineering 2012, 8, 45–58. [Google Scholar] [CrossRef]
- Wolf, K.L. Public response to the urban forest in inner-city business districts. J. Arboric. 2003, 29, 117–126. [Google Scholar]
- Wolch, J.R.; Byrne, J.; Newell, J.P. Urban green space, public health, and environmental justice: The challenge of making cities ‘just green enough’. Landsc. Urban Plan. 2014, 125, 234–244. [Google Scholar] [CrossRef] [Green Version]
- Pataki, D.E. Urban greening needs better data. Nature 2013, 502, 624. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ridd, M.K. Exploring a V-I-S (vegetation-impervious surface-soil) model for urban ecosystem analysis through remote sensing: Comparative anatomy for cities. Int. J. Remote Sens. 1995, 16, 2165–2185. [Google Scholar] [CrossRef]
- Li, L.; Lu, D.; Kuang, W. Examining urban impervious surface distribution and its dynamic change in Hangzhou metropolis. Remote Sens. 2016, 8, 265. [Google Scholar] [CrossRef] [Green Version]
- Lu, D.S.; Hetrick, S.; Moran, E. Impervious surface mapping with quickbird imagery. Int. J. Remote Sens. 2011, 32, 2519–2533. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lu, D.; Weng, Q. Use of impervious surface in urban land-use classification. Urban Urban Gree. 2006, 102, 146–160. [Google Scholar] [CrossRef]
- De la Barreraa, F.; Reyes-Paecke, S.; Banzhaf, E. Indicators for green spaces in contrasting urban settings. Ecol. Indic. 2016, 62, 212–219. [Google Scholar] [CrossRef]
- World Health Organization. Urban Planning, Environment and Health: From Evidence to Policy Action. 2010. 119. Available online: https://www.euro.who.int/en/home (accessed on 11 January 2020).
- Badiu, D.L.; Iojă, C.I.; Atroescu, M.P.; Breuste, J.; Artmann, M.; Niță, M.R.; Adinaru, S.R.G.; Hossu, C.A.; Onosea, D.A. Is urban green space per capita a valuable target to achieve cities’ sustainability goals? Romania as a case study. Ecol. Indic. 2016, 70, 53–66. [Google Scholar] [CrossRef]
- Kuang, W.; Chi, W.; Dengsheng, L.; Yinyin, D. A comparative analysis of megacity expansions in China and the U.S.: Patterns, rates and driving forces. Landsc. Urban Plan. 2014, 132, 121–135. [Google Scholar] [CrossRef]
- Cai, Y.; Chen, Y.; Tong, C. Spatiotemporal evolution of urban green space and its impact on the urban thermal environment based on remote sensing data: A case study of Fuzhou city, China. Urban. Urban Gree. 2019, 41, 333–343. [Google Scholar] [CrossRef]
- Sun, Y.; Xie, S.; Zhao, S. Valuing urban green spaces in mitigating climate change: A city—wide estimate of aboveground carbon stored in urban green spaces of China’s Capital. Glob. Chang. Biol. 2019, 25, 1717–1732. [Google Scholar] [CrossRef]
- Zhang, L.; Wang, Z.W.Z.; Da, L.D.L. Spatial characteristics of urban green space: A case study of Shanghai, China. Appl. Ecol. Environ. Res. 2019, 17, 1799–1815. [Google Scholar] [CrossRef]
- Huang, C.H.; Yang, J.; Jiang, P. Assessing impacts of urban form on landscape structure of urban green spaces in China using Landsat images based on Google Earth Engine. Remote Sens. 2018, 10, 1569. [Google Scholar] [CrossRef] [Green Version]
- Kong, F.H.; Nakagoshi, N. Spatial-temporal gradient analysis of urban green spaces in Jinan, China. Landsc. Urban Plan. 2006, 78, 147–164. [Google Scholar] [CrossRef]
- Zhang, X.; Guo, S.; Guan, Y.; Cai, D.; Zhang, C.; Flaus, K.; Xiao, H.; Tian, Z. Urbanization and spillover effect for three megaregions in China: Evidence from DMSP/OLS nighttime lights. Remote Sens. 2018, 10, 1888. [Google Scholar] [CrossRef] [Green Version]
- Zhao, J.; Chen, S.; Jiang, B.; Ren, Y.; Wang, H.; Vause, J.; Yu, H. Temporal trend of green space coverage in China and its relationship with urbanization over the last two decades. Sci. Total Environ. 2013, 442, 455–465. [Google Scholar] [CrossRef] [PubMed]
- Sun, J.; Wang, X.; Chen, A.; Ma, Y.; Cui, M.; Piao, S. NDVI indicated characteristics of vegetation cover change in China’s metropolises over the last three decades. Environ. Monit. Assess. 2011, 179, 1–14. [Google Scholar] [CrossRef] [PubMed]
- National Bureau of statistics of China. China Statistical Yearbook 2000; China Statistical Yearbook 2015; China Statistics Press: Beijing, China, 2001, 2016.
- Ning, J.; Liu, J.; Kuang, W.; Xu, X.; Zhang, S.; Yan, C.; Li, R.; Wu, S.; Hu, Y.; Du, G. Spatiotemporal patterns and characteristics of land-use change in China during 2010–2015. J. Geogr. Sci. 2018, 28, 547–562. [Google Scholar] [CrossRef] [Green Version]
- Kuang, W.; Liu, J.; Dong, J.; Chi, W.; Zhang, C. The rapid and massive urban and industrial land expansions in China between 1990 and 2010: A CLUD-based analysis of their trajectories, patterns, and drivers. Landsc. Urban Plan. 2016, 145, 21–33. [Google Scholar] [CrossRef]
- Liu, J.; Kuang, W.; Zhang, Z.; Xu, X.; Qin, Y.; Ning, J.; Zhou, W.; Zhang, S.; Li, R.; Yan, C. Spatiotemporal characteristics, patterns, and causes of land-use changes in China since the late 1980s. J. Geogr. Sci. 2014, 24, 195–210. [Google Scholar] [CrossRef]
- Kuang, W.; Yang, T.; Yan, F. Examining urban land-cover characteristics and ecological regulation during the construction of Xiong’an New District, Hebei Province, China. J. Geogr. Sci. 2018, 28, 109–123. [Google Scholar] [CrossRef] [Green Version]
- Dou, Y.; Kuang, W. A comparative analysis of urban impervious surface and green space and their dynamics among 318 different size cities in China in the past 25 years. Sci. Total Environ. 2019, 706, 135828. [Google Scholar] [CrossRef] [PubMed]
- Kuang, W.; Zhang, S.; Li, X.; Lu, D. A 30-meter resolution dataset of impervious surface area and green space fractions of China’s cities, 2000–2018. Earth Syst. Sci. Data Discuss. 2020. [Google Scholar] [CrossRef]
- Kuang, W. Mapping global impervious surface area and green space within urban environments. Sci. China Earth Sci. 2019, 62, 1–16. [Google Scholar] [CrossRef]
- Zhang, S.; Fang, C.; Kuang, W.; Sun, F. Comparison of changes in urban land use/cover and efficiency of megaregions in China from 1980 to 2015. Remote Sens. 2019, 11, 1834. [Google Scholar] [CrossRef] [Green Version]
- Pan, T.; Kuang, W.; Zhang, C.; Zhang, S.; Li, Z.; Chen, X. City-level comparison of urban land-cover configurations from 2000–2015 across 65 countries within the global Belt and Road. Remote Sens. 2019, 11, 1515. [Google Scholar] [CrossRef] [Green Version]
- McDonnell, M.J.; MacGregor-Fors, I. The ecological future of cities. Science 2016, 352, 936–938. [Google Scholar] [CrossRef]
- Wu, J.; Xiang, W.; Zhao, J. Urban ecology in China: Historical developments and future directions. Landsc. Urban Plan. 2014, 125, 222–233. [Google Scholar] [CrossRef]
- Pickett, S.; Cadenasso, M.; Grove, J.; Nilon, C.; Pouyat, R.; Zipperer, W.; Costanza, R. Urban ecological systems: Linking terrestrial ecological, physical, and socioeconomic components of metropolitan areas. Ann. Rev. Ecol. Syst. 2001, 32, 127–157. [Google Scholar] [CrossRef] [Green Version]
- Qiu, G.Y.; Zou, Z.; Li, X.; Li, H.; Guo, Q.; Yan, C.; Tan, S. Experimental studies on the effects of green space and evapotranspiration on urban heat island in a subtropical megacity in China. Habitat Int. 2017, 68, 30–42. [Google Scholar] [CrossRef]
- Hoag, H. How cities can beat the heat. Nature 2015, 524, 402–404. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ca, V.; Asaeda, T.; Abu, E. Reductions in air conditioning energy caused by a nearby park. Energ. Build. 1998, 29, 83–92. [Google Scholar] [CrossRef]
Zones | Selected Cities | Total Area of Built-Up Land (km2) | Urban Population (×104) |
---|---|---|---|
Coastal zone | 32 | 13,911.79 | 21,543.42 |
Northeastern zone | 10 | 2823.99 | 3049.79 |
Western zone | 15 | 3824.76 | 7508.64 |
Central zone | 13 | 3550.66 | 5276.78 |
City | Area of UGS in 2000 (km2) | Increment of UGS in 2000–2018 (km2) | Area of Built-Up Area in 2000 (km2) | Increase Increment of Built-Up Area in 2000–2018 (km2) |
---|---|---|---|---|
Beijing | 304.67 | 516.89 | 1034.95 | 1610.51 |
Nanjing | 88.95 | 159.20 | 348.70 | 537.41 |
Tianjin | 88.64 | 148.22 | 565.05 | 759.95 |
Shenzhen | 156.83 | 145.04 | 511.88 | 290.54 |
Changchun | 64.07 | 126.11 | 297.37 | 427.92 |
Guangzhou | 63.12 | 125.66 | 404.43 | 489.57 |
Jinan | 38.18 | 124.04 | 241.81 | 562.54 |
Shanghai | 155.21 | 119.51 | 778.06 | 294.01 |
Hefei | 31.79 | 117.28 | 150.15 | 442.97 |
Suzhou | 75.85 | 113.50 | 453.69 | 1154.96 |
Region | Area of UGS (km2) | Proportion of UGS (%) | |||
---|---|---|---|---|---|
2000 | 2018 | 2000–2018 | 2000 | 2018 | |
Coastal zone | 1675.77 | 4129.02 | 2453.25 | 28.24 | 29.68 |
Central zone | 318.67 | 881.63 | 562.96 | 23.69 | 24.83 |
Western zone | 415.55 | 922.15 | 506.60 | 25.27 | 24.11 |
Northeastern zone | 370.67 | 831.95 | 461.28 | 31.63 | 29.46 |
Total | 2780.66 | 6764.75 | 3984.09 | 27.54 | 28.06 |
Region | Proportion of UGS (%) | ||
---|---|---|---|
In Built-Up Areas in 2000 | In Newly Expanded Areas During 2000–2018 | In Built-Up Areas in 2018 | |
Coastal zone | 28.24 | 30.75 | 29.68 |
Central zone | 23.69 | 25.53 | 24.83 |
Western zone | 25.27 | 23.23 | 24.11 |
Northeastern zone | 31.63 | 27.92 | 29.46 |
Average of 70 cities | 27.54 | 28.43 | 28.06 |
City | UGS Area in 2018 Located in Built-Up Areas in 2000 | UGS Area in 2018 Located in Newly Expanded Areas in 2000–2018 | ||
---|---|---|---|---|
Area (km2) | Percentage (%) | Area (km2) | Percentage (%) | |
Beijing | 304.67 | 34.03 | 485.54 | 44.53 |
Changchun | 64.07 | 34.77 | 159.90 | 42.34 |
Nanjing | 88.95 | 33.03 | 156.50 | 35.11 |
Harbin | 57.21 | 35.12 | 155.97 | 48.04 |
Tianjin | 88.64 | 23.42 | 140.36 | 29.77 |
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Kuang, W.; Dou, Y. Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing. Remote Sens. 2020, 12, 1929. https://doi.org/10.3390/rs12121929
Kuang W, Dou Y. Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing. Remote Sensing. 2020; 12(12):1929. https://doi.org/10.3390/rs12121929
Chicago/Turabian StyleKuang, Wenhui, and Yinyin Dou. 2020. "Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing" Remote Sensing 12, no. 12: 1929. https://doi.org/10.3390/rs12121929