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Urban agglomeration of Kunming and Yuxi cities in Yunnan, China: the relative importance of government policy drivers and environmental constraints

  • Zhiming Zhang
  • Bin Wang
  • Alexander Buyantuev
  • Xiong He
  • Wei Gao
  • Yajin Wang
  • Dawazhaxi
  • Zijiang YangEmail author
Research Article
  • 78 Downloads

Abstract

Context

Political decisions and policies, as well as bio-physical factors are very important drivers of urban agglomeration, yet studies researching links between those factors, decision-making and landscape change associated with these processes are lacking.

Objectives

The objective of this study was to explore the urban agglomeration pattern and process of Kunming–Yuxi driven by recent political and economic decisions, as well as topographic factors.

Methods

We used multi-temporal Landsat imagery to create land cover maps and detect land cover changes from 2000 to 2015. The spatial trend surface analysis and lacunarity index were used to quantify the homogenization process of urbanization between Kunming and Yuxi.

Results

Land cover maps showed that built-up area increased remarkably reaching about 13% of the total area in 2015, and agricultural land declined from 12.2% in 2000 to 6.7% in 2015. Moreover, more than 90% of urban areas are located in flat areas. Spatial trends revealed the agglomeration of Kunming and Yuxi city. The lacunarity analysis also indicated that the homogeneity of built-up space increased resulting in increased connectivity of the cities.

Conclusions

Spatial trends and lacunarity analyses support the finding that moderate urban homogenization and agglomeration formation took place during the past 15 years. The “Integration of urban agglomeration of Kunming and Yuxi cities” agreement signed by the governments of the two cities in 2011, along with other similar policies, has contributed to the urban expansion. Moreover, because of the rough topography of Yunnan Plateau, the urban growth has also been shaped by topographic patterns.

Keywords

Urbanization Policy of Kunming–Yuxi city integration Lacunarity index Spatial trend surface analysis 

Notes

Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (41761040 and 41361046), and the foundation of Innovation in Culture Adaptation: Fostering Sustainable Community-Based Natural Resource Management in the South-Western Ethnic Minority Region, China (15XSH023). We are grateful for the kindness and generosity of people in the Government of Kunming City, Yunnan Province, who helped us conduct our work.

References

  1. Allain C, Cloitre M (1991) Characterizing the lacunarity of random and determined fractal sets. Phys Rev A 44:3552–3558CrossRefPubMedGoogle Scholar
  2. Atkinson PM, Tatnall ARL (1997) Introduction neural networks in remote sensing. Int J Remote Sens 18:699–709.  https://doi.org/10.1080/014311697218700 CrossRefGoogle Scholar
  3. Baigent E (2004) Patrick Geddes, Lewis Mumford and Jean Gottmann: divisions over ‘Megalopolis’. Prog Hum Geogr 28(6):687–700CrossRefGoogle Scholar
  4. Batten DF (1995) Network cities: creative urban agglomerations for the 21st century. Urban Stud 32(2):313–327CrossRefGoogle Scholar
  5. Benediktsson JA, Swain PH, Ersoy OK (1990) Neural network approaches versus statistical methods in classification of multisource remote sensing data. IEEE Trans Geosci Remote Sens 28(4):540-552CrossRefGoogle Scholar
  6. Braimoh AK, Onishi T (2007) Spatial determinants of urban land use change in Lagos, Nigeria. Land Use Policy 24(2):502-515CrossRefGoogle Scholar
  7. Bürgi M, Hersperger A, Schneeberger N (2004) Driving forces of landscape change: current and new directions. Landscape Ecol 19:857–868CrossRefGoogle Scholar
  8. Chen Y (2017) The research on the spatial evolution and maturation-degree of urban agglomerations in China. Master thesis, Peking University (in Chinese)Google Scholar
  9. Dale MRT (2000) Lacunarity analysis of spatial pattern: a comparison. Landscape Ecol 15:467–478CrossRefGoogle Scholar
  10. Ding Y, Peng J (2018) Impact of urbanization of mountainous areas on resources an environment: based on ecological footprint model. Sustainability 10:765.  https://doi.org/10.3390/su10030765 CrossRefGoogle Scholar
  11. Dong P (2009) Lacunarity analysis of raster datasets and 1D, 2D, and 3D point patterns. Comput Geosci 35:2100–2110CrossRefGoogle Scholar
  12. Duan D, Liu L (2012) Reflection On integrate development of neighboring cities. Planners 4:91–94 (in Chinese) Google Scholar
  13. Eastman JR (2016) Idrisi TerrSet user’s manual. Clark Labs, Clark University, WorcesterGoogle Scholar
  14. Fang C, Yu D (2017) Urban agglomeration: an evolving concept of an emerging phenomenon. Landsc Urban Plan 162:126–136CrossRefGoogle Scholar
  15. Feitelson E, Felsenstein D, Razin E, Stern E (2017) Assessing land use plan implementation: bridging the performance-conformance divide. Land Use Policy 61:251–264.  https://doi.org/10.1016/j.landusepol.2016.11.017 CrossRefGoogle Scholar
  16. Gennaio M (2008) Political driving forces of urban change in the region agglomeration Obersee. Dorctoral Thesis, Department of Geography, University of ZurichGoogle Scholar
  17. Grimm NB, Faeth SH, Golubiewski NE, Redman CL, Wu J, Bai X, Briggs JM (2008) Global change and the ecology of cities. Science 319(5864):756–760CrossRefPubMedGoogle Scholar
  18. Gu CL, Wu LY, Cook L (2012) Progress in research on Chinese urbanization. Front Archit Res 1:101–149CrossRefGoogle Scholar
  19. Han J, Kamber M (2001) Data mining: concepts and techniques. Academic Press, San DiegoGoogle Scholar
  20. Jiang W, Chen Z, Lei X, He B, Jia K, Zhang Y (2016) Simulation of urban agglomeration ecosystem spatial distributions under different scenarios: a case study of the Changsha–Zhuzhou–Xiangtan urban agglomeration. Ecol Eng 88:112–121CrossRefGoogle Scholar
  21. Kipnis BA (1997) Dynamics and potentials of Israel’s megalopolitan processes. Urban Stud 34(3):489–501CrossRefGoogle Scholar
  22. Kuang W, Chi W, Lu D, Dou Y (2014) A comparative analysis of megacity expansions in China and the U.S.: patterns, rates and driving forces. Landsc Urban Plan 132:121–135CrossRefGoogle Scholar
  23. Li GD, Sun S, Fang CL (2018) The varying driving forces of urban expansion in China: insights from a spatial-temporal analysis. Landsc Urban Plan 174:63–77CrossRefGoogle Scholar
  24. Li XM, Zhou WQ, Ouyang ZY (2013) Forty years of urban expansion in Beijing: what is the relative importance of physical, socioeconomic, and neighborhood factors? Appl Geogr 38:1–10CrossRefGoogle Scholar
  25. Liu Y, Peng J, Zhang T, Zhao M (2016a) Assessing landscape eco-risk associated with hilly construction land exploitation in the southwest of China: trade-off and adaptation. Ecol Ind 62:289–297CrossRefGoogle Scholar
  26. Liu J, Zhan J, Deng X (2005) Spatio-temporal patterns and driving forces of urban land expansion in China during the economic reform era. Ambio 34(6):450–455CrossRefPubMedGoogle Scholar
  27. Liu M, Zhang Z, Zhang H, Yang M, Song D, Ou X (2016b) Spatial-temporal monitoring of urban growth: a case in Kunming, southwest China. In: Bian F, Xie Y (eds) Geo-informatics in resource management and sustainable ecosystem. Communications in computer and information science, vol 569. Springer, BerlinGoogle Scholar
  28. Long Y, Gu Y, Han H (2012) Spatiotemporal heterogeneity of urban planning implementation effectiveness: evidence from five urban master plans of Beijing. Landsc Urban Plan 108(2–4):103–111CrossRefGoogle Scholar
  29. Mas JF, Flores JJ (2008) The application of artificial neural networks to the analysis of remotely sensed data. Int J Remote Sens 29:617–663CrossRefGoogle Scholar
  30. McIntyre NE, Wiens JA (2000) A novel use of the lacunarity index to discernlandscape function. Landscape Ecol 15:313–321CrossRefGoogle Scholar
  31. Müller K, Steinmeier C, Küchler M (2010) Urban growth along motorways in Switzerland. Landsc Urban Plan 98:3–12CrossRefGoogle Scholar
  32. National Bureau of Statistics of the people’s Republic of China (2017) Tabulation on the 2010 population census of the People’s Republic of China. http://www.stats.gov.cn/tjsj/pcsj/rkpc/6rp/indexch.htm. Accessed 5 Sept 2017
  33. Peng J, Du Y, Liu Y, Hu X (2016a) How to assess urban development potential in mountain areas? An approach of ecological carrying capacity in the view of couples human and natural systems. Ecol Ind 60:1017–1030CrossRefGoogle Scholar
  34. Peng J, Ma J, Du Y, Zhang L, Hu X (2016b) Ecological suitability evaluation for mountainous area development based on conceptual model of landscape structure, function, and dynamics. Ecol Ind 61:500–511CrossRefGoogle Scholar
  35. Peng J, Wu JS, Yin H, Li ZG, Chang Q, Mu TL (2008) Rural land use change during 1986–2002 in Lijiang, China, based on remote sensing and GIS data. Sensors 8:8201–8223CrossRefPubMedGoogle Scholar
  36. Peng J, Zhao M, Guo X, Pan Y, Liu Y (2017) Spatial-temporal dynamics and associated driving forces of urban ecological land: a case study in Shenzhen City, China. Habitat Int 60:81–90CrossRefGoogle Scholar
  37. Plotnick RE, Garden RH, Hargrove WW, Prestegaard K, Perlmutter M (1996) Lacunarity analysis: a general technique for the analysis of spatial patterns. Phys Rev E 53(5):5461–5468CrossRefGoogle Scholar
  38. Pontius RG (2000) Quantification error versus location error in comparison of categorical maps. Photogramm Eng Remote Sens 66:1011–1016Google Scholar
  39. Pontius RG (2002) Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions. Photogramm Eng Remote Sens 68:1041–1049Google Scholar
  40. Rahman MR, Saha SK (2009) Spatial dynamics of cropland and cropping pattern change analysis using Landsat TM and IRS P6 LISS III satellite images with GIS. Geo-spat Inf Sci 12(2):123–134CrossRefGoogle Scholar
  41. Roces-Diaz JV, Diaz-Varela E, Alvarez-Alvarez P (2014) Analysis of spatial for ecosystem services: application of the lacunarity concept at landscape level in Galicia (NW Spain). Ecol Ind 36:495–507CrossRefGoogle Scholar
  42. Schneeberger N, Bürgi M, Hersperger A, Ewald KC (2007) Driving forces and rates of landscape change as a promising combination for landscape change research: an application on the northern fringe of the Swiss Alps. Land Use Policy 24:349–361CrossRefGoogle Scholar
  43. Seto KC, Fragkias M, Güneralp B, Reilly MK (2011) A meta-analysis of global urban land expansion. PLoS ONE 6(8):e23777CrossRefPubMedPubMedCentralGoogle Scholar
  44. Sexton JO, Song X, Huang C, Channan S, Baker ME, Townshend JR (2013) Urban growth of the Washington, D.C.-Baltimore, MD metropolitan region from 1984 to 2010 by annual, Landsat-based estimates of imperious cover. Remote Sens Environ 129:42–53CrossRefGoogle Scholar
  45. Thiha, Webb EL, Honda K (2007) Biophysical and policy drivers of landscape change in a central Vietnamese district. Environ Conserv 34(2):164–172CrossRefGoogle Scholar
  46. Tian L, Shen T (2011) Evaluation of plan implementation in the transitional China: a case of Guangzhou city master plan. Cities 28(1):11-27CrossRefGoogle Scholar
  47. United Nations (2012) World urbanization prospects: the 2011 revision. http://www.esa.un.org/unpd/wup/index.htm. Accessed 25 July 2012
  48. Wang M, Krstikj A, Koura H (2017) Effects of urban planning on urban expansion control in Yinchuan City, Western China. Habitat Int 64:85-97CrossRefGoogle Scholar
  49. Wei C, Taubenböck H, Blaschke T (2017) Measuring urban agglomeration using a city-scale dasymetric population map: a study in the Pearl River Delta, China. Habitat Int 59:32–43CrossRefGoogle Scholar
  50. Wu JG (2008) Making the case for landscape ecology: an effective approach to urban sustainability. Landsc J 27(1):41–50CrossRefGoogle Scholar
  51. Wu JG (2010) Urban sustainability: an inevitable goal of landscape research. Landscape Ecol 25:1–4CrossRefGoogle Scholar
  52. Wu J, Jenerette GD, Buyantuyev A, Redman CL (2011) Quantifying spatiotemporal patterns of urbanization: the case of the two fastest growing metropolitan regions in the United States. Ecol Complex 8(1):1–8CrossRefGoogle Scholar
  53. Wu JG, He CY, Huang GL, Yu DY (2013) Urban landscape ecology: past, present, and future. In: Fu B, Jones B (eds) Landscape ecology for sustainable environment and culture. Springer, Dordrecht, pp 37–53CrossRefGoogle Scholar
  54. Wu JG, Xiang WN, Zhao JZ (2014) Urban ecology in China: historical developments and future directions. Landsc Urban Plan 125:222–233CrossRefGoogle Scholar
  55. Wu WJ, Zhao SQ, Zhu C, Jiang JL (2015) A comparative study of urban expansion in Beijing, Tianjin and Shijiazhuang over the past three decades. Landsc Urban Plan 134:93–106CrossRefGoogle Scholar
  56. Yang YM, Tian K, Hao JM, Pei SJ, Yang YX (2004) Biodiversity and biodiversity conservation in Yunnan, China. Biodivers Conserv 13:813–826CrossRefGoogle Scholar
  57. Yin H, Kong F, Yang X, James P, Dronova I (2018) Exploring zoning scenario impacts upon urban growth simulations using a dynamic spatial model. Cities 81:214–229CrossRefGoogle Scholar
  58. Yu W, Zhou W (2018) Spatial pattern of urban change in two Chinese megaregions: contrasting responses to national policy and economic mode. Sci Total Environ 634:1362–1371CrossRefPubMedGoogle Scholar
  59. Zhang Z, Su S, Xiao R, Jiang D, Wu J (2013) Identifying determinants of urban growth from a multi-scale perspective: a case study of the urban agglomeration around Hangzhou Bay, China. Appl Geogr 45:193–202CrossRefGoogle Scholar
  60. Zhang Z, Van Coillie F, Ou X, De Wulf R (2014) Integration of satellite imagery, topography and human disturbance factors based on canonical correspondence analysis ordination for mountain vegetation mapping: a case study in Yunnan, China. Remote Sens 6(2):1026–1056CrossRefGoogle Scholar
  61. Zhang L, Zhao SX (2003) Reinterpretation of China’s under-urbanization: a systemic perspective. Habitat Int 27:459–483CrossRefGoogle Scholar
  62. Zhou WQ, Huang G, Pickett S, Cadenasso M (2011) 90 years of forest cover change in an urbanizing watershed: spatial and temporal dynamics. Landscape Ecol 26(5):645–659CrossRefGoogle Scholar
  63. Zhou WQ, Jiao M, Yu WJ, Wang J (2019) Urban sprawl in a megaregion: a multiple spatial and temporal perspective. Ecol Ind 96:54–66.  https://doi.org/10.1016/j.ecolind.2017.10.035 CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.School of Ecology and Environmental Sciences and Yunnan Key Laboratory for Plateau Mountain Ecology and Restoration of Degraded EnvironmentsYunnan UniversityKunmingChina
  2. 2.Department of Geography and PlanningUniversity at AlbanyAlbanyUSA
  3. 3.School of Architecture and PlanningYunnan UniversityKunmingChina

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