Urbanization that hides in the dark – Spotting China’s “ghost neighborhoods” from space

Shi, Lifeng; Wurm, Michael; Huang, Xianjin; Zhong, Taiyang; Leichtle, Tobias; Taubenböck, Hannes

doi:10.1016/j.landurbplan.2020.103822

Cited by 34 publications

(19 citation statements)

References 41 publications

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“…In the future, studies could collect successive years of built‐up data using MLEI proposed by Jiao et al., 2015 to effectively overcome this defect. Additionally, concerning the identification of ghost cities, our research focuses more on the idleness of buildings; if more of the emerging geographic big data will support it, this can be extended to a neighborhood scale (Shi et al., 2020). From the theoretical standpoint, we did not further explore the pathways, mechanisms, and theoretical relationships of UGPs and building distribution patterns.…”

Section: Discussionmentioning

confidence: 99%

Comparisons of three‐dimensional urban forms in different urban expansion types: 58 sample cities in China

Rao

Zhou

et al. 2020

Growth and Change

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Section: Discussionmentioning

confidence: 99%

Comparisons of three‐dimensional urban forms in different urban expansion types: 58 sample cities in China

Rao

Zhou

et al. 2020

Growth and Change

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“…Hence, using composited NTL data from multiple sources might assure the robustness of consistent time-series images. In addition, China's "ghost neighborhoods" phenomenon has been identified in dynamic regions, such as YRD and GBA [82], which might underestimate the NTL intensity. Therefore, further studies that combine NTL images with real-world activity intensity are desirable.…”

Section: Limitations and Future Studymentioning

confidence: 99%

Spatiotemporal Patterns of Urbanization in the Three Most Developed Urban Agglomerations in China Based on Continuous Nighttime Light Data (2000–2018)

Gao

et al. 2021

Remote Sensing

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Urban agglomeration is an advanced spatial form of integrating cities, resulting from the global urbanization of recent decades. Understanding spatiotemporal patterns and evolution is of great importance for improving urban agglomeration management. This study used continuous time-series NTL data from 2000 to 2018 combined with land-use images to investigate the spatiotemporal patterns of urbanization in the three most developed urban agglomerations in China over the past two decades: the Beijing–Tianjin–Hebei urban agglomeration (BTH), the Yangtze River Delta urban agglomeration (YRD), and the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). The NTL intensity indexes, dynamic thresholds, extracted urban areas, and landscape metrics were synthetically used to facilitate the analysis. This study found that the urbanization process in the study areas could be divided into three stages: rapid urbanization in core cities from 2000 to 2010, a fluctuating urbanization process in both core cities and surrounding cities from 2010 to 2015, and stable urbanization, mainly in surrounding cities with a medium size after 2015. Meanwhile, the urbanization level of GBA was higher than that of YRD and BTH. However, with the acceleration of urban development in YRD, the gap in the urbanization level between GBA and YRD narrowed significantly in the third stage. In addition, this study confirmed that the scattered, medium-sized cities in YRD and GBA were more developed than those in BTH. This study showed that continuous NTL data could be effectively applied to monitor the urbanization patterns of urban agglomerations.

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“…This leads to “phantom urbanisation” characterised by “face projects” that often do not live up to expectations but create “an urban façade” (Sorace and Hurst, 2016: 306). While the real extent and spatial distribution of this phenomenon is a matter of debate (Li, 2017; Shi et al, 2020; Tan et al, 2020), there is widespread consensus and even official acknowledgement by China’s leadership that the “urbanisation of land has outpaced the urbanisation of the population” (土地城镇化快于人口城镇化, State Council, 2014: chapter 2). The main driver of this phenomenon is the land-based finance system of most local governments (Yep, 2019).…”

Section: Empty Villages Empty Citiesmentioning

confidence: 99%

“…At the same time, China’s urbanisation drive has been unprecedented in scale. Environmental scholar Vaclav Smil calculated that China used more cement within three years (2011–2013) than the USA did over the whole of the twentieth century (cited in Shi et al, 2020: 1). In view of this, China’s urbanisation has also produced some paradoxical outcomes and led to multiple interconnections between the rural and the urban spheres.…”

mentioning

confidence: 99%

China’s Rural–Urban Transformation: New Forms of Inclusion and Exclusion

Alpermann

2020

Journal of Current Chinese Affairs

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China’s urbanisation drive has been unprecedented in scale. It has also produced some paradoxical outcomes and led to multiple interconnections between the rural and the urban spheres. These interconnections are the central focus of this special issue. Thus, preference is given to the term “rural–urban transformation” instead of simply “urbanisation.” The main argument advanced here is that we always need to consider the rural aspects and repercussions alongside the urban side of this dual process. This introduction first highlights some of these antinomies to set the stage for the discussion. Next, it explains how they relate to changing mechanisms of inclusion/exclusion. It is proposed that a theoretical approach of functional differentiation can help us sort out the various ways inclusions and exclusions are being produced and combined. Finally, the introduction presents an overview of the articles collected in this special issue and how they relate to the aforementioned topics.

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Urbanization that hides in the dark – Spotting China’s “ghost neighborhoods” from space

Cited by 34 publications

References 41 publications

Comparisons of three‐dimensional urban forms in different urban expansion types: 58 sample cities in China

Comparisons of three‐dimensional urban forms in different urban expansion types: 58 sample cities in China

Spatiotemporal Patterns of Urbanization in the Three Most Developed Urban Agglomerations in China Based on Continuous Nighttime Light Data (2000–2018)

China’s Rural–Urban Transformation: New Forms of Inclusion and Exclusion

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