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Evaluation of three-dimensional urban expansion: A case study of Yangzhou City, Jiangsu Province, China

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Abstract

With rapid urban development in China in the last two decades, the three-dimensional (3D) characteristic has been the main feature of urban morphology. However, the vast majority of researches of urban growth have focused on the planar area (two-dimensional (2D)) expansion. Few studies have been conducted from a 3D perspective. In this paper, the 3D urban expansion of the Yangzhou City, Jiangsu Province, China from 2003 to 2012 was evaluated based on Geographical Information System (GIS) tools and high-resolution remote sensing images. Four indices, namely weighted average height of buildings, volume of buildings, 3D expansion intensity and 3D fractal dimension are used to quantify the 3D urban expansion. The weighted average height of buildings and the volume of buildings are used to illustrate the temporal change of the 3D urban morphology, while the other two indices are used to calculate the expansion intensity and the fractal dimension of the 3D urban morphology. The results show that the spatial distribution of the high-rise buildings in Yangzhou has significantly spread and the utilization of the 3D space of Yangzhou has become more efficient and intensive. The methods proposed in this paper laid a foundation for a wide range of study of 3D urban morphology changes.

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References

  • Bai Y Q, He G J, 2011. Application of region growing algorithm in extracting heights of buildings from high resolution satellite images. In: Image and Signal Processing (CISP), 2011 4 th International Congress on. IEEE, 2: 879–882. doi: 10.1109/CISP.2011.6100334

    Article  Google Scholar 

  • Batty M, Longley P, 1994. Fractal Cities: A Geometry of Form and Function. London: Academic Press.

    Google Scholar 

  • Benguigui L, Czamanski D, Marinov M et al., 2000. When and where is a city fractal? Environment and Planning B: Planning and Design, 27(4): 507–519. doi: 10.1068/b2617

    Article  Google Scholar 

  • Cai B, Zhang Z, Liu B et al., 2007. Spatial-temporal changes of Tianjin urban spatial morphology from 1978 to 2004. Journal of Geographical Sciences, 17(4): 500–510. doi: 10.1007/s11442-007-0500-4

    Article  Google Scholar 

  • Dare P M, 2005. Shadow analysis in high-resolution satellite imagery of urban areas. Photogrammetric Engineering and Remote Sensing, 71: 169–177.

    Article  Google Scholar 

  • Fan F, Wang Y, Qiu M et al., 2009. Evaluating the temporal and spatial urban expansion patterns of Guangzhou from 1979 to 2003 by remote sensing and GIS methods. International Journal of Geographical Information Science, 23(11): 1371–1388. doi: 10.1080/13658810802443432

    Article  Google Scholar 

  • Frankhauser P, 1998. The fractal approach. A new tool for the spatial analysis of urban agglomerations. Population: An English Selection, 10: 205–240.

    Google Scholar 

  • Herold M, Goldstein N C, Clarke K C, 2003. The spatiotemporal form of urban growth: Measurement, analysis and modeling. Remote Sensing of Environment, 86(3): 286–302. doi: 10.1016/S0034-4257(03)00075-0

    Article  Google Scholar 

  • Hu Z L, Du P J, Guo D Z, 2007. Analysis of urban expansion and driving forces in Xuzhou city based on remote sensing. Journal of China University of Mining and Technology, 17(2): 267–271. doi: 10.1016/S1006-1266(07)60086-8

    Article  Google Scholar 

  • Huang J, Lu X, Sellers J M, 2007. A global comparative analysis of urban form: Applying spatial metrics and remote sensing. Landscape and Urban Planning, 82(4): 184–197. doi: 10.1016/j.landurbplan.2007.02.010

    Article  Google Scholar 

  • Feng J, 2003. Spatial-temporal evolution of urban morphology and land use structure in Hangzhou. Acta Geographica Sinica, 58(3): 343–353. (in Chinese)

    Google Scholar 

  • Liu S, Fan X, Wen Q et al., 2012. Simulated impacts of 3D urban morphology on urban transportation in megacities: Case study in Beijing. International Journal of Digital Earth, (ahead-of-print): 1–22. doi: 10.1080/17538947.2012.740079

    Google Scholar 

  • Ma R, Gu C, Pu Y et al., 2008. Mining the urban sprawl pattern: A case study on Sunan, China. Sensors, 8(10): 6371–6395. doi: 10.3390/s8106371

    Article  Google Scholar 

  • Massalabi A, He D C, Benie G B et al., 2004. Detecting information under and from shadow in panchromatic Ikonos images of the city of Sherbrooke. In Geoscience and Remote Sensing Symposium, 2004. IGARSS’04. Proceedings. 2004 IEEE International, 3: 2000–2003. doi: 10.1109/IGARSS. 2004.1370740

    Article  Google Scholar 

  • Pan X Z, Zhao Q G, Chen J et al., 2008. Analyzing the variation of building density using high spatial resolution satellite images: The example of Shanghai City. Sensors, 8(4): 2541–2550. doi: 10.3390/s8042541

    Article  Google Scholar 

  • Pham H M, Yamaguchi Y, Bui T Q, 2011. A case study on the relation between city planning and urban growth using remote sensing and spatial metrics. Landscape and Urban Planning, 100: 223–230. doi: 10.3390/s8042541

    Article  Google Scholar 

  • Riitters K H, O’neill R, Hunsaker C et al., 1995. A factor analysis of landscape pattern and structure metrics. Landscape Ecology, 10(1): 23–39. doi: 10.1007/BF00158551

    Article  Google Scholar 

  • Rottensteiner F, 2003. Automatic generation of high-quality building models from lidar data. Computer Graphics and Applications, IEEE, 23(6): 42–50. doi: 10.1109/MCG.2003.1242381

    Article  Google Scholar 

  • Rottensteiner F, Briese C, 2002. A new method for building extraction in urban areas from high-resolution LIDAR data. International Archives of Photogrammetry Remote Sensing and Spatial Information Sciences, 34: 295–301.

    Google Scholar 

  • Seto K C, Fragkias M, Güneralp B et al., 2011. A meta-analysis of global urban land expansion. PlosOne, 6(8): e23777. doi: 10.1371/journal.pone.0023777

    Article  Google Scholar 

  • Shen G, 2002. Fractal dimension and fractal growth of urbanized areas. International Journal of Geographical Information Science, 16(5): 419–437. doi: 10.1080/13658810210137013

    Article  Google Scholar 

  • Shen J, Wong K, Feng Z, 2002. State-sponsored and spontaneous urbanization in the Pearl River Delta of south China, 1980-1998. Urban Geography, 23(7): 674–694. doi: 10.2747/0272-3638.23.7.674

    Article  Google Scholar 

  • Sun C, Wu Z F, Lv Z Q et al., 2013. Quantifying different types of urban growth and the change dynamic in Guangzhou using multi-temporal remote sensing data. International Journal of Applied Earth Observation and Geoinformation, 21: 409–417. doi: 10.1016/j.jag.2011.12.012

    Article  Google Scholar 

  • Sun P J, Song W, Xiu C L et al., 2013. Non-coordination in China’s urbanization: Assessment and affecting factors. Chinese Geographical Science, 23(6): 729–739. doi: 10.1007/s11769-013-0634-5

    Article  Google Scholar 

  • Tannier C, Pumain D, 2005. Fractals in urban geography: A theoretical outline and an empirical example. Cybergeo: European Journal of Geography. doi: 10.4000/cybergeo.3275

    Google Scholar 

  • Wang Deli, Fang Chuanglin, Gao Boyang et al., 2011. Measurement and spatio-temporal distribution of urbanization development quality of urban agglomeration in China. Chinese Geographical Science, 21(6): 695–707. doi: 10.1007/s11769-011-0477-x

    Article  Google Scholar 

  • Wang Y, Fang C L, Sheng C Y, 2013. Spatial differentiation and model evolution of housing prices in Yangzhou. Acta Geographic Sinica, 68(8): 1082–1096. (in Chinese)

    Google Scholar 

  • Xiao J, Shen Y, Ge J et al., 2006. Evaluating urban expansion and land use change in Shijiazhuang, China, by using GIS and remote sensing. Landscape and Urban Planning, 75(1–2): 69–80. doi: 10.1016/j.landurbplan.2004.12.005

    Article  Google Scholar 

  • Yangzhou Statistical Bureau, 2013. Yangzhou Statistical Yearbook. Beijing: China Statistics Press.

    Google Scholar 

  • Yoshida H, Omae M, 2005. An approach for analysis of urban morphology: Methods to derive morphological properties of city blocks by using an urban landscape model and their interpretations. Computers, Environment and Urban Systems, 29(2): 223–247. doi: 10.1109/IGARSS.2004.1370740

    Article  Google Scholar 

  • Yu B, Liu H, Wu J et al., 2010. Automated derivation of urban building density information using airborne LiDAR data and object-based method. Landscape and Urban Planning, 98(3–4): 210–219. doi: 10.1016/j.landurbplan.2010.08.004

    Article  Google Scholar 

  • Zhang L, Wu J, Zhen Y et al., 2004. A GIS-based gradient analysis of urban landscape pattern of Shanghai metropolitan area, China. Landscape and Urban Planning, 69(1): 1–16. doi: 10.1016/j.landurbplan.2003.08.006

    Article  Google Scholar 

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Authors and Affiliations

  1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Jing Qin, Chuanglin Fang, Guangdong Li & Shaojian Wang

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Jing Qin, Guangdong Li & Shaojian Wang

  3. Guangzhou Institute of Geography, Guangzhou, 510070, China

    Yang Wang

Authors
  1. Jing Qin
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  2. Chuanglin Fang
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  3. Yang Wang
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  4. Guangdong Li
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  5. Shaojian Wang
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Corresponding author

Correspondence to Chuanglin Fang.

Additional information

Foundation item: Under the auspices of Major Project of National Social Science Foundation of China (No. 13&ZD13027), National Science & Technology Pillar Program During 12th Five-year Plan Period (No. 2012BAJ22B03-04), National Natural Science Foundation of China (No. 41401164)

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Qin, J., Fang, C., Wang, Y. et al. Evaluation of three-dimensional urban expansion: A case study of Yangzhou City, Jiangsu Province, China. Chin. Geogr. Sci. 25, 224–236 (2015). https://doi.org/10.1007/s11769-014-0728-8

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  • DOI: https://doi.org/10.1007/s11769-014-0728-8

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