Exploring complex urban growth and land use efficiency in China’s developed regions: implications for territorial spatial planning

Xiaolu TANG , Li SHENG , Yinkang ZHOU

Front. Earth Sci. ›› 2022, Vol. 16 ›› Issue (4) : 1040 -1051.

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Front. Earth Sci. ›› 2022, Vol. 16 ›› Issue (4) : 1040 -1051. DOI: 10.1007/s11707-022-0973-6
RESEARCH ARTICLE
RESEARCH ARTICLE

Exploring complex urban growth and land use efficiency in China’s developed regions: implications for territorial spatial planning

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Abstract

Developed regions in China have experienced rapid urban expansion and have consequently induced a series of challenging environmental issues since its economic reform and opening-up. Taking Zhejiang as a case study area, the present paper explores the complex types of urban growth over the last four decades as well as land use efficiency. Moreover, it discusses the implications of the aforementioned on China National territorial spatial planning (TSP). The acquired results have shown that: 1) urban expansion has slowed down, exhibiting a three-stage trend of “slight increase (1980−1990)—dramatic growth (1990−2010)—slow growth (after 2010)”; 2) the complex types of urban growth reveal that the urban diffusion has been gradually controlled and the urban form tends to be more condensed; and 3) the mean values for pure technical efficiency (PTE) and scale efficiency (SE) of urban land use are 0.83 and 0.95 respectively, indicating PTE as the main factor restricting the improvement of urban land use. Based on these results, some beneficial policy implications and suggestions for TSP are provided. First, it is suggested that “Inventory Planning” will be the main direction of TSP other than “Incremental Planning”. Secondly, we should pay more attention to the protection of cultivated land and ecological resources. Lastly, TSP should guide the economic growth away from simply relying on resource inputs and steer it toward technology and capital investment.

Keywords

urban expansion / urban growth types / land use efficiency / Zhejiang / territorial spatial planning

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Xiaolu TANG, Li SHENG, Yinkang ZHOU. Exploring complex urban growth and land use efficiency in China’s developed regions: implications for territorial spatial planning. Front. Earth Sci., 2022, 16(4): 1040-1051 DOI:10.1007/s11707-022-0973-6

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References

[1]

Ai B,, Ma C,, Zhao J,, Zhang R. ( 2020). The impact of rapid urban expansion on coastal mangroves: a case study in Guangdong Province, China. Front Earth Sci, 14( 1): 37– 49

[2]

Bailey T C, Gatrell A C ( 1995). Interactive Spatial Data Analysis. Essex: Longman Scientific & Technical

[3]

Birch C, Oom S P, Beecham J A ( 2007). Rectangular and hexagonal grids used for observation, experiment and simulation in ecology. Ecol Modell, 206( 3−4): 347− 359

[4]

Brenner N,, Schmid C. ( 2014). The ‘urban age’ in question. Int J Urban Reg Res, 38( 3): 731– 755

[5]

Chen J,, Chen J,, Liao A,, Cao X,, Chen L,, Chen X,, He C,, Han G,, Peng S,, Lu M,, Zhang W,, Tong X,, Mills J. ( 2015). Global land cover mapping at 30m resolution: a POK-based operational approach. ISPRS J Photogramm Remote Sens, 103: 7– 27

[6]

Chen Y,, Chen Z,, Xu G,, Tian Z. ( 2016). Built-up land efficiency in urban China: insights from the general land use plan (2006–2020). Habitat Int, 51: 31– 38

[7]

Corbane C,, Pesaresi M,, Kemper T,, Politis P,, Florczyk A,, Syrris V,, Melchiorri M,, Sabo F,, Soille P. ( 2019). Automated global delineation of human settlements from 40 years of Landsat satellite data archives. Big Earth Data, 3( 2): 140– 169

[8]

Cui X,, Li S,, Wang X,, Xue X. ( 2019). Driving factors of urban land growth in Guangzhou and its implications for sustainable development. Front Earth Sci, 13( 3): 464– 477

[9]

DeFries R S,, Rudel T K,, Uriarte M,, Hansen M. ( 2010). Deforestation driven by urban population growth and agricultural trade in the twenty-first century. Nat Geosci, 3( 3): 178– 181

[10]

Du J,, Fu Q,, Fang S,, Wu J,, He P,, Quan Z. ( 2019). Effects of rapid urbanization on vegetation cover in the metropolises of China over the last four decades. Ecol Indic, 107: 105458

[11]

Färe R,, Grosskopf S. ( 1997). Intertemporal production frontiers: with dynamic DEA. J Oper Res Soc, 48( 6): 656

[12]

Feng Y,, Wu S,, Wu P,, Su S,, Weng M,, Bian M. ( 2018). Spatiotemporal characterization of megaregional poly-centrality: evidence for new urban hypotheses and implications for polycentric policies. Land Use Policy, 77: 712– 731

[13]

Henderson J V. ( 2003). The urbanization process and economic growth: the so-what question. J Econ Growth, 8( 1): 47– 71

[14]

Hu Y,, Wang F,, Guin C,, Zhu H. ( 2018). A spatio-temporal kernel density estimation framework for predictive crime hotspot mapping and evaluation. Appl Geogr, 99: 89– 97

[15]

Huo Z,, Guo S. ( 2020). Research on spatial mismatch and optimal allocation of basic education facilities under the perspective of inventory planning: take Anshan city as an example. Urban Develop Studies, 27( 6): 1– 6

[16]

Jia S,, Wang C,, Li Y,, Zhang F,, Liu W. ( 2017). The urbanization efficiency in Chengdu City: an estimation based on a three-stage DEA model. Phys Chem Earth Parts ABC, 101: 59– 69

[17]

Jin Y,, Liang J,, Wang J,, Song M,, Shen J. ( 2019). Study on the multi-land use and functional complex in country parks under inventory planning development background—taking Shanghai suburban regulation unit as an example. Chin Landscape Architect, 35( 02): 33– 38

[18]

Kew B,, Lee B. ( 2013). Measuring sprawl across the urban rural continuum using an amalgamated sprawl index. Sustainability, 5( 5): 1806– 1828

[19]

Li H,, Xu X,, Li X,, Ma S,, Zhang H. ( 2021). Characterizing the urban spatial structure using taxi trip big data and implications for urban planning. Front Earth Sci, 15( 1): 70– 80

[20]

Li X,, Gong P. ( 2016). Urban growth models: progress and perspective. Sci Bull (Beijing), 61( 21): 1637– 1650

[21]

Li Y,, Song J. ( 2020). Effects of stock-based planning from the perspective of multistakeholder governance: a case study on the regeneration project of Hubei Village in Shenzhen. City Plan Rev, 44( 9): 120– 124

[22]

Liu S,, Xiao W,, Li L,, Ye Y,, Song X. ( 2020). Urban land use efficiency and improvement potential in China: a stochastic frontier analysis. Land Use Policy, 99: 105046

[23]

Liu X,, Li X,, Chen Y,, Tan Z,, Li S,, Ai B. ( 2010). A new landscape index for quantifying urban expansion using multi-temporal remotely sensed data. Landsc Ecol, 25( 5): 671– 682

[24]

Liu Y,, Zhou Y. ( 2021). Territory spatial planning and national governance system in China. Land Use Policy, 102: 105288

[25]

Northam R M ( 1975). Urban Geography. New York: John Wiley & Sons

[26]

Peng J,, Hu Y,, Liu Y,, Ma J,, Zhao S. ( 2018). A new approach for urban-rural fringe identification: integrating impervious surface area and spatial continuous wavelet transform. Landsc Urban Plan, 175: 72– 79

[27]

Qiao W,, Hu Y,, Jia K,, He T,, Wang Y. ( 2020). Dynamic modes and ecological effects of salt field utilization in the Weifang coastal area, China: implications for territorial spatial planning. Land Use Policy, 99: 104952

[28]

Qiu L,, Pan Y,, Zhu J,, Amable G S,, Xu B. ( 2019). Integrated analysis of urbanization-triggered land use change trajectory and implications for ecological land management: a case study in Fuyang, China. Sci Total Environ, 660: 209– 217

[29]

Richards T,, Gallego J,, Achard F. ( 2000). Sampling for forest cover change assessment at the pan-tropical scale. Int J Remote Sens, 21( 6−7): 1473– 1490

[30]

Schneider A,, Friedl M A,, Potere D. ( 2010). Mapping global urban areas using MODIS 500-m data: new methods and datasets based on ‘urban ecoregions’. Remote Sens Environ, 114( 8): 1733– 1746

[31]

Su S,, Wang Y,, Luo F,, Mai G,, Pu J. ( 2014). Peri-urban vegetated landscape pattern changes in relation to socioeconomic development. Ecol Indic, 46: 477– 486

[32]

Tan K,, Zhou S,, Li E,, Du P. ( 2015). Assessing the impact of urbanization on net primary productivity using multi-scale remote sensing data: a case study of Xuzhou, China. Front Earth Sci, 9( 2): 319– 329

[33]

Tan S,, Hu B,, Kuang B,, Zhou M. ( 2021). Regional differences and dynamic evolution of urban land green use efficiency within the Yangtze River Delta, China. Land Use Policy, 106: 105449

[34]

Timmer M P,, Los B. ( 2005). Localized innovation and productivity growth in Asia: an intertemporal DEA approach. J Prod Anal, 23( 1): 47– 64

[35]

United Nations ( 2019). World Urbanization Prospects: The 2018 Revision. New York

[36]

Wang P,, Zeng C,, Song Y,, Guo L,, Liu W,, Zhang W. ( 2021). The spatial effect of administrative division on land-use intensity. Land (Basel), 10( 5): 543

[37]

Wu W,, Zhao H,, Jiang S. ( 2018). A Zipf’s Law-Based method for mapping urban areas using NPP-VIIRS nighttime light data. Remote Sens, 10( 1): 130

[38]

Xinhua Agency ( 2019a). Opinions of the CPC Central Committee and the State Council on the establishment and supervision of territorial space planning system. Available at Xinhuanet website

[39]

Xinhua Agency ( 2019b). Guiding opinions of the CPC Central Committee and the State Council on the overall delimitation and implementation of three control lines in territorial space planning. Available at the State Council website

[40]

Zeng J,, Zhang R,, Tang J,, Liang J,, Li J,, Zeng Y,, Li Y,, Zhang Q,, Shui W,, Wang Q. ( 2021). Ecological sustainability assessment of the carbon footprint in Fujian Province, southeast China. Front Earth Sci, 15( 1): 12– 22

[41]

Zhang W,, Xu H. ( 2017). Effects of land urbanization and land finance on carbon emission: a panel data analysis for Chinese provinces. Land Use Policy, 63: 493– 500

[42]

Zhao Z,, Zheng X,, Fan H,, Sun M. ( 2021). Urban spatial structure analysis: quantitative identification of urban social functions using building footprints. Front Earth Sci, 15( 3): 507– 525

[43]

Zheng Z,, Wu Z,, Chen Y,, Yang Z,, Marinello F. ( 2020). Detection of city integration processes in rapidly urbanizing areas based on remote sensing imagery. Land (Basel), 9( 10): 378

[44]

Zhong T,, Huang X,, Wang B. ( 2010). On the degrees of decoupling and re-coupling of economic growth and expansion of construction land in China from 2002 to 2007. J Nat Resourc, 25: 18– 31

[45]

Zhu X,, Li Y,, Zhang P,, Wei Y,, Zheng X,, Xie L. ( 2019). Temporal–spatial characteristics of urban land use efficiency of China’s 35 mega cities based on DEA: decomposing technology and scale efficiency. Land Use Policy, 88: 104083

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