IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i10p1103-d659341.html
   My bibliography  Save this article

Mixed Land Use Evaluation and Its Impact on Housing Prices in Beijing Based on Multi-Source Big Data

Author

Listed:
  • Hanbing Yang

    (School of Land Science and Technology, China University of Geosciences, Beijing 100083, China)

  • Meichen Fu

    (School of Land Science and Technology, China University of Geosciences, Beijing 100083, China)

  • Li Wang

    (State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China)

  • Feng Tang

    (School of Land Science and Technology, China University of Geosciences, Beijing 100083, China)

Abstract

The tense relationship between the supply and demand of land resources and the past spatial expansion of urban development in Beijing have brought many urban problems. Mixed land use is considered to be able to solve these urban problems as well as promote sustainable urban development. In this context, this study uses multi-source big data such as POI, OpenStreetMap and web crawler data to construct current land-use data of the area within the sixth ring road of Beijing, and then uses the entropy index and type number index to analyze the spatial distribution and aggregation characteristics of the mixed land-use level. Finally, a multi-scale geographically weighted regression is applied to explore the impact of the block and life circle scale mixed land use on housing prices. The results show that: (1) the accuracy of land use data obtained by using multi-source big data is high, and the consistency with the real land use situation is as high as 82.67%. (2) the mixed land use level in the study area is higher in the urban center and lower in the periphery of the city. However, it does not show the spatial distribution characteristics gradually decreasing with the increase of the distance from the urban center but shows that the area from the third to the fifth ring road is the highest. (3) the impact of block scale and life circle scale mixed land use on housing price is different. The type number index has a negative effect on the housing price in block scale mixed land use, while the entropy index has a positive effect on the housing price in life circle scale mixed land use. Based on the existing “bottom-up” individual-dominant development mode, the government of Beijing should issue relevant policies and documents to give “top-down” control and guidance in the future, so as to promote the maximization of the benefits of mixed land use. Furthermore, in the practice of mixed land use in Beijing, land use types should be reduced at the block scale and the area of different land use types should be balanced at the life circle scale.

Suggested Citation

  • Hanbing Yang & Meichen Fu & Li Wang & Feng Tang, 2021. "Mixed Land Use Evaluation and Its Impact on Housing Prices in Beijing Based on Multi-Source Big Data," Land, MDPI, vol. 10(10), pages 1-21, October.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:10:p:1103-:d:659341
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/10/1103/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/10/10/1103/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Danya Kim & Jangik Jin, 2019. "The Effect of Land Use on Housing Price and Rent: Empirical Evidence of Job Accessibility and Mixed Land Use," Sustainability, MDPI, vol. 11(3), pages 1-18, February.
    2. Hans R.A. Koster & Jan Rouwendal, 2012. "The Impact Of Mixed Land Use On Residential Property Values," Journal of Regional Science, Wiley Blackwell, vol. 52(5), pages 733-761, December.
    3. Ying Long & Xingjian Liu, 2013. "Featured Graphic. How Mixed is Beijing, China? A Visual Exploration of Mixed Land Use," Environment and Planning A, , vol. 45(12), pages 2797-2798, December.
    4. John Matthews & Geoffrey Turnbull, 2007. "Neighborhood Street Layout and Property Value: The Interaction of Accessibility and Land Use Mix," The Journal of Real Estate Finance and Economics, Springer, vol. 35(2), pages 111-141, August.
    5. Chris Jacobs-Crisioni & Piet Rietveld & Eric Koomen & Emmanouil Tranos, 2014. "Evaluating the Impact of Land-Use Density and Mix on Spatiotemporal Urban Activity Patterns: An Exploratory Study Using Mobile Phone Data," Environment and Planning A, , vol. 46(11), pages 2769-2785, November.
    6. Kim Dovey & Elek Pafka, 2017. "What is functional mix? An assemblage approach," Planning Theory & Practice, Taylor & Francis Journals, vol. 18(2), pages 249-267, April.
    7. Raman, Rewati & Roy, Uttam Kumar, 2019. "Taxonomy of urban mixed land use planning," Land Use Policy, Elsevier, vol. 88(C).
    8. Gu, Donghwan & Newman, Galen & Kim, Jun-Hyun & Park, Yunmi & Lee, Jaekyung, 2019. "Neighborhood decline and mixed land uses: Mitigating housing abandonment in shrinking cities," Land Use Policy, Elsevier, vol. 83(C), pages 505-511.
    9. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
    10. Song, Yan & Knaap, Gerrit-Jan, 2003. "New urbanism and housing values: a disaggregate assessment," Journal of Urban Economics, Elsevier, vol. 54(2), pages 218-238, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zengzheng Wang & Fuhao Zhang & Yangyang Zhao, 2023. "Exploring the Spatial Discrete Heterogeneity of Housing Prices in Beijing, China, Based on Regionally Geographically Weighted Regression Affected by Education," Land, MDPI, vol. 12(1), pages 1-24, January.
    2. Fangyuan Liu & Kaili Chen & Tianzheng Zhang & Yingjie Zhang & Yan Song, 2022. "Will Good Service Quality Promote Real Estate Value? Evidence from Beijing, China," Land, MDPI, vol. 11(2), pages 1-18, January.
    3. Yunes Almansoub & Ming Zhong & Asif Raza & Muhammad Safdar & Abdelghani Dahou & Mohammed A. A. Al-qaness, 2022. "Exploring the Effects of Transportation Supply on Mixed Land-Use at the Parcel Level," Land, MDPI, vol. 11(6), pages 1-28, May.
    4. Xia, Fangzhou & Lu, Pingzhen, 2023. "Can mixed land use promote social integration? Multiple mediator analysis based on spatiotemporal big data in Beijing," Land Use Policy, Elsevier, vol. 132(C).
    5. Yanzhe Cui & Pengjun Zhao & Ling Li & Juan Li & Mingyuan Gong & Yiling Deng & Zihuang Si & Shuaichen Yan & Xuewei Dang, 2024. "A new model for residential location choice using residential trajectory data," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    6. Eliza Szczerek, 2021. "The Problem of Densification of Large-Panel Housing Estates upon the Example of Cracow," Land, MDPI, vol. 10(12), pages 1-23, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yunes Almansoub & Ming Zhong & Asif Raza & Muhammad Safdar & Abdelghani Dahou & Mohammed A. A. Al-qaness, 2022. "Exploring the Effects of Transportation Supply on Mixed Land-Use at the Parcel Level," Land, MDPI, vol. 11(6), pages 1-28, May.
    2. Hongji Chen & Kangchuan Su & Lixian Peng & Guohua Bi & Lulu Zhou & Qingyuan Yang, 2022. "Mixed Land Use Levels in Rural Settlements and Their Influencing Factors: A Case Study of Pingba Village in Chongqing, China," IJERPH, MDPI, vol. 19(10), pages 1-18, May.
    3. Danya Kim & Jangik Jin, 2019. "The Effect of Land Use on Housing Price and Rent: Empirical Evidence of Job Accessibility and Mixed Land Use," Sustainability, MDPI, vol. 11(3), pages 1-18, February.
    4. Ekaterina Chernobai & Michael Reibel & Michael Carney, 2011. "Nonlinear Spatial and Temporal Effects of Highway Construction on House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 42(3), pages 348-370, April.
    5. Alessia Iannillo & Isidoro Fasolino, 2021. "Land-Use Mix and Urban Sustainability: Benefits and Indicators Analysis," Sustainability, MDPI, vol. 13(23), pages 1-18, December.
    6. Hee Jin Yang & Jihoon Song & Mack Joong Choi, 2016. "Measuring the Externality Effects of Commercial Land Use on Residential Land Value: A Case Study of Seoul," Sustainability, MDPI, vol. 8(5), pages 1-15, April.
    7. Hongyu Zheng & Yuefei Zhuo & Zhongguo Xu & Cifang Wu & Jianhong Huang & Qi Fu, 2021. "Measuring and characterizing land use mix patterns of China’s megacities: A case study of Shanghai," Growth and Change, Wiley Blackwell, vol. 52(4), pages 2509-2539, December.
    8. Yang Xiao & Chris Webster & Scott Orford, 2016. "Identifying house price effects of changes in urban street configuration: An empirical study in Nanjing, China," Urban Studies, Urban Studies Journal Limited, vol. 53(1), pages 112-131, January.
    9. Yuchen Qin & Yikang Zhang & Minfeng Yao & Qiwei Chen, 2023. "How to Measure the Impact of Walking Accessibility of Suburban Rail Station Catchment Areas on the Commercial Premium Benefits of Joint Development," Sustainability, MDPI, vol. 15(6), pages 1-29, March.
    10. Jeremy Gabe & Spenser Robinson & Andrew Sanderford, 2022. "Willingness to Pay for Attributes of Location Efficiency," The Journal of Real Estate Finance and Economics, Springer, vol. 65(3), pages 384-418, October.
    11. Xuanxuan Xia & Kexin Lin & Yang Ding & Xianlei Dong & Huijun Sun & Beibei Hu, 2020. "Research on the Coupling Coordination Relationships between Urban Function Mixing Degree and Urbanization Development Level Based on Information Entropy," IJERPH, MDPI, vol. 18(1), pages 1-24, December.
    12. Christopher Bitter, 2014. "Subdivision Vintage and Housing Prices: Do Home Buyers Value Traditional Development?," Urban Studies, Urban Studies Journal Limited, vol. 51(5), pages 1038-1056, April.
    13. Terrence M. Clauretie & Herman Li, 2019. "Land Values: Size Matters," The Journal of Real Estate Finance and Economics, Springer, vol. 58(1), pages 80-110, January.
    14. Julia Freybote & Hua Sun & Xi Yang, 2015. "The Impact of LEED Neighborhood Certification on Condo Prices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 43(3), pages 586-608, September.
    15. Yunes Almansoub & Ming Zhong & Muhammad Safdar & Asif Raza & Abdelghani Dahou & Mohammed A. A. Al-qaness, 2023. "Modeling Impact of Transportation Infrastructure-Based Accessibility on the Development of Mixed Land Use Using Deep Neural Networks: Evidence from Jiang’an District, City of Wuhan, China," Sustainability, MDPI, vol. 15(21), pages 1-40, October.
    16. Fahad Ahmed Shaikh & Mir Aftab Hussain Talpur & Imtiaz Ahmed Chandio & Saima Kalwar, 2022. "Factors Influencing Residential Location Choice towards Mixed Land-Use Development: An Empirical Evidence from Pakistan," Sustainability, MDPI, vol. 14(21), pages 1-25, November.
    17. Yencha, Christopher, 2019. "Valuing walkability: New evidence from computer vision methods," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 689-709.
    18. Likun Wu & Wei Lang & Tingting Chen, 2024. "Deciphering Urban Land Use Patterns in the Shenzhen–Dongguan Cross-Boundary Region Based on Multisource Data," Land, MDPI, vol. 13(2), pages 1-24, January.
    19. Bridgelall, Raj & Stubbing, Edward, 2021. "Forecasting the effects of autonomous vehicles on land use," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    20. Velma Zahirovic-Herbert & Karen M Gibler, 2022. "The effect of film production studios on housing prices in Atlanta, the Hollywood of the South," Urban Studies, Urban Studies Journal Limited, vol. 59(4), pages 771-788, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:10:y:2021:i:10:p:1103-:d:659341. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.