Chinese Geographical Science

, Volume 29, Issue 5, pp 848–860 | Cite as

Accessibility Comparison and Spatial Differentiation of Xi’an Scenic Spots with Different Modes Based on Baidu Real-time Travel

  • Li WangEmail author
  • Xiaoshu Cao
  • Tao Li
  • Xingchuan Gao


A study of the accessibility of a city’s scenic spots via different travel modes can contribute to optimization of tourism-related transportation while improving tourists’ travel-related satisfaction levels and advancing tourism. We systematically analyzed the accessibility of 56 scenic spots in Xi’an City, China, via car and public transport travel modes using the real-time travel function of the Baidu Maps API (Application Programming Interface) along with spatial analysis methods and the modal accessibility gap index of scenic spots. We obtained the following results. First, maximum and minimum travel times using public transport exceeded those using cars. Moreover, the accessibility of scenic spots via cars and public transport presented a circular spatial pattern of increasing travel time from the center to the periphery. Contrasting with travel by public transport, car travel showed a clear time-space compression effect. Second, accessibility of the scenic spots via cars and public transport showed some spatial heterogeneity, with no clear advantages of car accessibility in the central urban area. However, advantages of car accessibility were increasingly evident moving from the center to the periphery. Third, whereas the correlation of the modal accessibility gap index of scenic spots in Xi’an with global space was significantly positive, local spatial interdependence was only evident in some inner city areas and in marginal areas. Moreover, spatial heterogeneity was evident in two regions but was insignificant in other areas, indicating that the spatial interdependence of the modal accessibility gap index in most scenic spots was not apparent in terms of the overall effect of public transport routes, road networks, and the distribution of scenic spots. The improvement of public transport coverage in marginal areas and the optimization of public transport routes in central urban areas are essential tasks for improving travel using public transport in the future.


Baidu real-time travel car accessibility public transport accessibility modal accessibility gap scenic spots Xi’an City 


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  1. AlKahtani S J H, Xia J H, Veenendaaland B et al., 2015. Building a conceptual framework for determining individual differences of accessibility to tourist attractions. Tourism Management Perspectives, 16: 28–42. doi: 10.1016/j.tmp.2015.05.002CrossRefGoogle Scholar
  2. Anselin L, 1995. Local indicators of spatial association-LISA. Geographical Analysis, 27(2): 93–115. doi: 10.1111/j.1538-4632.1995.tb00338.xCrossRefGoogle Scholar
  3. Bao Jigang, Chu Yifang, 2012. Tourism Geography. 3rd ed. Beijing: Higher Education Press, 329. (in Chinese)Google Scholar
  4. Bifulco G N, Leone S, 2014. Exploiting the accessibility concept for touristic mobility. Procedia-Social and Behavioral Sciences, 111: 432–439. doi: 10.1016/j.sbspro.2014.01.076CrossRefGoogle Scholar
  5. Burns L D, Golob T F, 1976. The role of accessibility in basic transportation choice behavior. Transportation, 5(2): 175–198. doi: 10.1007/BF00167272CrossRefGoogle Scholar
  6. Cao Fangdong, Huang Zhenfang, Wu Jiang et al., 2012. The relationship between tourism efficiency measure and location accessibility of Chinese national scenic areas. Acta Geographica Sinica, 67(12): 1686–1697. (in Chinese)Google Scholar
  7. China Industry Information Network, 2018. Analysis of tourist market reception and total income in Xi’an of China in 2017. Avalliable at (in Chinese)Google Scholar
  8. Gaman G, Răcăşan B, 2016. Transport accessibility as a factor for tourism flow augmentation. Case study: the Romanian health resorts. Journal of Settlements and Spatial Planning, 7(1): 65–77. doi: 10.19188/07JSSP012016Google Scholar
  9. Guo Jianke, Wang Shaobo, Wang Hui et al., 2016. Impact of Harbin-Dalian high-speed railway on the spatial distribution of tourism supply and demand markets in Northeast China cities: based on the accessibility of the scenic spots. Progress in Geography, 35(4): 505–514. (in Chinese)CrossRefGoogle Scholar
  10. Hansen W G, 1959. How accessibility shapes land use. Journal of the American Institute of Planners, 25(2): 73–76. doi: 10.1080/01944365908978307CrossRefGoogle Scholar
  11. Hess D B, 2005. Access to employment for adults in poverty in the Buffalo-Niagara region. Urban Studies, 42(7): 1177–1200. doi: 10.1080/00420980500121384CrossRefGoogle Scholar
  12. Hooper J, 2015. A destination too far? Modelling destination accessibility and distance decay in tourism. GeoJournal, 80(1): 33–46. doi: 10.1007/s10708-014-9536-zCrossRefGoogle Scholar
  13. Huang Yinghuai, Liu Xiaoping, Liu Yanping et al., 2018. Spatial and temporal accessibility analysis of urban parks based on Amap API by means of multiple transportation: a case study of Haizhu district in Guangzhou. Geography and Geo-Information Science, 34(6): 50–57. (in Chinese)Google Scholar
  14. Ingram D R, 1971. The concept of accessibility: a search for an operational form. Regional Studies, 5(2): 101–107. doi: 10.1080/09595237100185131CrossRefGoogle Scholar
  15. Jiang Haibing, Liu Jianguo, Jiang Jinliang, 2014. An analysis of the accessibility of China’s tourist attractions under the impact of high-speed railway. Tourism Tribune, 29(7): 58–67. (in Chinese)Google Scholar
  16. Jin Cheng, Lu Yuqi, Zhang Li et al., 2009. An analysis of accessibility of scenic spots based on land traffic network: a case study of Nanjing. Geographical Research, 28(1): 246–258. (in Chinese)Google Scholar
  17. Jin Cheng, Huang Zhenfang, 2012. Tourism regionalization in the Yangtze River Delta based on accessibility. Geographical Research, 31(4): 745–757. (in Chinese)Google Scholar
  18. Johnston R J, 2004. The Dictionary of Human Geography. Chai Yanwei, trans. Beijing: The Commercial Press. (in Chinese)Google Scholar
  19. Kawabata M, Shen Q, 2007. Commuting inequality between cars and public transit: the case of the San Francisco bay area, 1990–2000. Urban Studies, 44(9): 1759–1780. doi: 10.1080/00420980701426616CrossRefGoogle Scholar
  20. Kawabata M, 2009. Spatiotemporal dimensions of modal accessibility disparity in Boston and San Francisco. Environment and Planning A: Economy and Space, 41(1): 183–198. doi: 10.1068/a4068CrossRefGoogle Scholar
  21. Kwok R C W, Yeh A G O, 2004. The use of modal accessibility gap as an indicator for sustainable transport development. Environment and Planning A: Economy and Space, 36(5): 921–936. doi: 10.1068/a3673CrossRefGoogle Scholar
  22. Levinson D M, 1998. Accessibility and the journey to work. Journal of Transport Geography, 6(1): 11–21. doi: 10.1016/ S0966-6923(97)00036-7CrossRefGoogle Scholar
  23. Li Li, Wang Degen, 2012. The impact of urban low-carbon public transport to tourist attractions’ accessibility—Suzhou city area as the example. Economic Geography, 32(3): 166–172. (in Chinese)Google Scholar
  24. Lv Tao, Cao Youhui, 2010. Construction of spatial autocorrelation method of spatial-temporal proximity and its application: taking regional economic disparity in the Yangtze River Delta as a case study. Geographical Research, 29(2): 351–360. (in Chinese)Google Scholar
  25. Moran P A P, 1948. The interpretation of statistical maps. Journal of the Royal Statistical Society. Series B, 10(2): 243–251.Google Scholar
  26. Pan Jinghu, Cong Yibo, 2014. Tourism regionalization in China based on spatial accessibility of A-grade scenic spots. Scientia Geographica Sinica, 34(10): 1161–1168. (in Chinese)Google Scholar
  27. Pan Jinghu, Li Junfeng, 2014. Spatial distribution characteristics and accessibility of A-grade tourist attractions in China. Journal of Natural Resources, 29(1): 55–66. (in Chinese)Google Scholar
  28. Qin Wenmin, Zhang Xiaolei, Yang Zhaoping et al., 2015. Accessibility of tourism transport based on link performance function— a case of 3A tourism scenic spots in Xinjiang. Arid Zone Research, 32(2): 361–367. (in Chinese)Google Scholar
  29. Salonen M, Toivonen T, 2013. Modelling travel time in urban networks: comparable measures for private car and public transport. Journal of Transport Geography, 31: 143–153. doi: 10.1016/j.jtrangeo.2013.06.011CrossRefGoogle Scholar
  30. Shen Q, 2001. A spatial analysis of job openings and access in a U.S. metropolitan area. Journal of the American Planning Association, 67(1): 53–68. doi: 10.1080/01944360108976355CrossRefGoogle Scholar
  31. Silva C, Pinho P, 2010. The structural accessibility layer (SAL): revealing how urban structure constrains travel choice. Environment and Planning A: Economy and Space, 42(11): 2735–2752. doi: 10.1068/a42477CrossRefGoogle Scholar
  32. Sun Jianwei, Tian Ye, Cui Jiaxing et al., 2017. Identification of tourism spatial structure and measurement of tourism spatial accessibility in Hubei Province. Economic Geography, 37(4): 208–217. (in Chinese)Google Scholar
  33. Tóth G, Dávid L, 2010. Tourism and accessibility: an integrated approach. Applied Geography, 30(4): 666–677. doi: 10.1016/ j.apgeog.2010.01.008CrossRefGoogle Scholar
  34. Xi’an Local Chronicle Office, 2017. Xi’an Yearbook (2016).Google Scholar
  35. Xi’an: World Publishing Xi’an Co. Ltd. 188−192. (in Chinese)Google Scholar
  36. Xi’an Local Chronicle Office, 2018. Xi’an Yearbook (2017).Google Scholar
  37. Xi’an: World Publishing Xi’an Co. Ltd. 189−193. (in Chinese)Google Scholar
  38. Yang Ming, Zhang Rui, 2016. In 2016, The tourism revenue of Xi’an reached 120 billion yuan and tourists reached 150 million. Xi’an News Network. Avaliable at 2016-12-17. (in Chinese)Google Scholar
  39. Uchiyama Y, Kohsaka R, 2016. Cognitive value of tourism resources and their relationship with accessibility: a case of Noto region, Japan. Tourism Management Perspectives, 19: 61–68. doi: 10.1016/j.tmp.2016.03.006CrossRefGoogle Scholar
  40. Yang W Y, Chen B Y, Cao X S et al., 2017. The spatial characteristics and influencing factors of modal accessibility gaps: a case study for Guangzhou, China. Journal of Transport Geography, 60: 21–32. doi: 10.1016/j.jtrangeo.2017.02.005CrossRefGoogle Scholar
  41. Yang Xiaozhong, Feng Lixin, Zhang Kai, 2013. The impact of transportation on accessibility of tourism scenic region of cross-border tourism region: a case study of Dabieshan Mountain. Scientia Geographica Sinica, 33(6): 693–702. (in Chinese)CrossRefGoogle Scholar
  42. Zhang Qi, Xie Shuangyu, Wang Xiaofang et al., 2015. Evaluation on the accessibility of the scenic spots in Wuhan based on the spatial syntax. Economic Geography, 35(8): 200–208. (in Chinese)Google Scholar
  43. Zhong Yexi, Liu Ying, Lai Geying, 2011. The study on accessibility and spatial structures for red tourist attractions in Jiangxi province. Journal of Jiangxi Normal University (Natural Science), 35(2): 208–212. (in Chinese)Google Scholar

Copyright information

© Science Press, Northeast Institute of Geography and Agroecology, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Geography and TourismShaanxi Normal UniversityXi’anChina
  2. 2.Tourism College and Institute of Human GeographyXi’an International Studies UniversityXi’anChina
  3. 3.Northwest Land and Resource Research CentreShaanxi Normal UniversityXi’anChina

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