Abstract
Urban greenspace, as an essential component of green infrastructure, is particularly important in the urban environment that maintains the function and sustainability of urbanities. With the rapid economic growth over recent decades, China has been experiencing unprecedented urbanisation processes, at the same time, led to dramatic changes in urban land use and living environment. Therefore, understanding the spatiotemporal changes of urban greenspace coverage and how they impact on population’s exposure to urban greenspace is a critical requirement for supporting urban planning and healthy city development. Although a number of studies have attempted to evaluate urban greenspace changes in China, a comprehensive and multidimensional assessment of urban greenspace coverage and exposure is still lacking. Meanwhile, the emerging geospatial big data provides unique opportunities to quantify the interaction between human activities and the green environment, which has been limitedly addressed. In this chapter, we retrospect some of our recent works on leveraging multi-source remote sensing and social big data to estimate the dynamics of greenspace coverage and exposure change for Chinese large cities. The expected findings will advance our understanding of the following questions in a more systematic way: (1) What is the spatiotemporal pattern of greenspace changes over the past two decades? (2) What is the temporal dynamic and heterogeneity in greenspace exposure? (3) How does urban expansion impact on greenspace exposure experience? (4) Are there any inequalities in greenspace exposure among Chinese cities?
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Benton-Short L, Keeley M, Rowland J (2019) Green infrastructure, green space, and sustainable urbanism: geography’s important role. Urban Geogr 40:330–351
Chen B, Nie Z, Chen Z, Xu B (2017) Quantitative estimation of 21st-century urban greenspace changes in Chinese populous cities. Sci Total Environ 609:956–965
Chen B, Song Y, Huang B, Xu B (2020) A novel method to extract urban human settlements by integrating remote sensing and mobile phone locations. Sci Remote Sens 100003
Chen B, Song Y, Jiang T, Chen Z, Huang B, Xu B (2018a) Real-time estimation of population exposure to PM2. 5 using Mobile-and station-based big data. Int J Env Res Public Health 15:573
Chen B, Song Y, Kwan M-P, Huang B, Xu B (2018b) How do people in different places experience different levels of air pollution? Using worldwide Chinese as a lens. Environ Pollut 238:874–883
Dallimer M, Tang Z, Bibby PR, Brindley P, Gaston KJ, Davies ZG (2011) Temporal changes in greenspace in a highly urbanized region. Biol Let 7:763–766
De Ridder K, Adamec V, Bañuelos A, Bruse M, Bürger M, Damsgaard O, Dufek J, Hirsch J, Lefebre F, Pérez-Lacorzana J (2004) An integrated methodology to assess the benefits of urban green space. Sci Total Environ 334:489–497
Deng J, Huang Y, Chen B, Tong C, Liu P, Wang H, Hong Y (2019a) A methodology to monitor urban expansion and green space change using a time series of multi-sensor SPOT and Sentinel-2A images. Remote Sens 11:1230
Deng S, Ma J, Zhang L, Jia Z, Ma L (2019b) Microclimate simulation and model optimization of the effect of roadway green space on atmospheric particulate matter. Environ Pollut 246:932–944
Ernstson H (2013) The social production of ecosystem services: a framework for studying environmental justice and ecological complexity in urbanized landscapes. Landsc Urban Plan 109:7–17
Fung T, So L, Chen Y, Shi P, Wang J (2008) Analysis of green space in Chongqing and Nanjing, cities of China with ASTER images using object-oriented image classification and landscape metric analysis. Int J Remote Sens 29:7159–7180
Heynen N, Perkins HA, Roy P (2006) The political ecology of uneven urban green space: the impact of political economy on race and ethnicity in producing environmental inequality in Milwaukee. Urban Aff Rev 42:3–25
Irvine KN, Devine-Wright P, Payne SR, Fuller RA, Painter B, Gaston KJ (2009) Green space, soundscape and urban sustainability: an interdisciplinary, empirical study. Local Environ 14:155–172
Kabisch N, Haase D (2013) Green spaces of European cities revisited for 1990–2006. Landsc Urban Plan 110:113–122
McConnachie MM, Shackleton CM (2010) Public green space inequality in small towns in South Africa. Habitat Int 34:244–248
Mitchell R, Popham F (2008) Effect of exposure to natural environment on health inequalities: an observational population study. The Lancet 372:1655–1660
Nowak DJ, Greenfield EJ (2012) Tree and impervious cover in the United States. Landsc Urban Plan 107:21–30
Ow LF, Ghosh S (2017) Urban cities and road traffic noise: reduction through vegetation. Appl Acoust 120:15–20
Peng S, Piao S, Ciais P, Friedlingstein P, Ottle C, Bréon F-M, Nan H, Zhou L, Myneni RB (2012) Surface urban heat island across 419 global big cities. Environ Sci Technol 46:696–703
Schipperijn J, Bentsen P, Troelsen J, Toftager M, Stigsdotter UK (2013) Associations between physical activity and characteristics of urban green space. Urban Forest Urban Green 12:109–116
Small C (2003) High spatial resolution spectral mixture analysis of urban reflectance. Remote Sens Environ 88:170–186
Song Y, Chen B, Kwan M-P (2020) How does urban expansion impact people’s exposure to green environments? A comparative study of 290 Chinese cities. J Clean Prod 246:119018
Song Y, Huang B, Cai J, Chen B (2018) Dynamic assessments of population exposure to urban greenspace using multi-source Big Data. Sci Total Environ 634:1315–1325
Su JG, Dadvand P, Nieuwenhuijsen MJ, Bartoll X, Jerrett M (2019) Associations of green space metrics with health and behavior outcomes at different buffer sizes and remote sensing sensor resolutions. Environ Int 126:162–170
Sun J, Wang X, Chen A, Ma Y, Cui M, Piao S (2011) NDVI indicated characteristics of vegetation cover change in China’s metropolises over the last three decades. Environ Monit Assess 179:1–14
Sun S, Xu X, Lao Z, Liu W, Li Z, García EH, He L, Zhu J (2017) Evaluating the impact of urban green space and landscape design parameters on thermal comfort in hot summer by numerical simulation. Build Environ 123:277–288
Van Renterghem T (2019) Towards explaining the positive effect of vegetation on the perception of environmental noise. Urban Forest Urban Green 40:133–144
Wang X, Zhang C, Hasi E, Dong Z (2010) Has the Three Norths Forest Shelterbelt Program solved the desertification and dust storm problems in arid and semiarid China? J Arid Environ 74:13–22
Wendel HEW, Zarger RK, Mihelcic JR (2012) Accessibility and usability: green space preferences, perceptions, and barriers in a rapidly urbanizing city in Latin America. Landsc Urban Plan 107:272–282
Wolch JR, Byrne J, Newell JP (2014) Urban green space, public health, and environmental justice: the challenge of making cities ‘just green enough.’ Landsc Urban Plan 125:234–244
Wu W, Yao Y, Song Y, He D, Wang R (2021) Perceived influence of street-level visible greenness exposure in the work and residential environment on life satisfaction: Evidence from Beijing, China. Urban Forest Urban Green 127161
Wüstemann H, Kalisch D, Kolbe J (2017) Access to urban green space and environmental inequalities in Germany. Landsc Urban Plan 164:124–131
Xing Y, Brimblecombe P (2019) Role of vegetation in deposition and dispersion of air pollution in urban parks. Atmos Environ 201:73–83
Acknowledgements
This study is supported by The University of Hong Kong HKU-100 Scholars Fund and the National Natural Science Foundation of China (Grant NO. 42001385).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Chen, B., Song, Y. (2022). Changes of Urban Greenspace Coverage and Exposure in China. In: Cheshmehzangi, A. (eds) Green Infrastructure in Chinese Cities. Urban Sustainability. Springer, Singapore. https://doi.org/10.1007/978-981-16-9174-4_8
Download citation
DOI: https://doi.org/10.1007/978-981-16-9174-4_8
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-9173-7
Online ISBN: 978-981-16-9174-4
eBook Packages: Social SciencesSocial Sciences (R0)