IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i17p4624-d260906.html
   My bibliography  Save this article

Investigating Road-Constrained Spatial Distributions and Semantic Attractiveness for Area of Interest

Author

Listed:
  • Hongtao Ma

    (School of Tourism and Geography Science, Yunnan Normal University, Kunming 650500, China
    Center for Myanmar Studies of Yunnan Normal University, Kunming 650500, China)

  • Yuan Meng

    (College of Geography and Environment, Shandong Normal University, Jinan 250300, Shandong, China
    Research and Development Centre for Big Geo-Data, Shandong Normal University, Jinan 250300, Shandong, China)

  • Hanfa Xing

    (College of Geography and Environment, Shandong Normal University, Jinan 250300, Shandong, China
    Research and Development Centre for Big Geo-Data, Shandong Normal University, Jinan 250300, Shandong, China)

  • Cansong Li

    (School of Tourism and Geography Science, Yunnan Normal University, Kunming 650500, China
    Center for Myanmar Studies of Yunnan Normal University, Kunming 650500, China)

Abstract

An area of interest (AOI) refers to an urban area that attracts people’s attention within different urban functions through cities. The wide availability of big geo-data that are able to capture human activities and environmental socioeconomics enable a more nuanced identification of AOIs. Current research has proposed various approaches to delineate continuous AOI patterns using big geo-data. However, these approaches ignore the effects of urban structures such as road networks on reshaping AOIs, and fail to investigate the attractiveness and certain functions within AOIs. To fill this gap, this paper proposes a systematic framework to investigate the spatial distribution of road-constrained AOIs and analyze the semantic attractiveness. First, we propose an Epanechnikov-based kernel density estimation (KDE) with a bandwidth selection strategy to extract road-constrained AOIs. Then, we establish semantic attractiveness indices regarding AOIs based on the textual information and the number of review data. Finally, we investigate in detail the spatial distribution and semantic attractiveness of AOIs in Yuexiu, Guangzhou. The results show that road-constrained AOIs can not only effectively capture the human activity patterns influenced by urban structures, but also depict certain urban functions including entertainment, public, service, hotel, education, and food functions. This method provides a quantitative reference to monitor urban structures and human activities to support city planning.

Suggested Citation

  • Hongtao Ma & Yuan Meng & Hanfa Xing & Cansong Li, 2019. "Investigating Road-Constrained Spatial Distributions and Semantic Attractiveness for Area of Interest," Sustainability, MDPI, vol. 11(17), pages 1-15, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:17:p:4624-:d:260906
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/17/4624/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/17/4624/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yu, Wenhao & Ai, Tinghua & Shao, Shiwei, 2015. "The analysis and delimitation of Central Business District using network kernel density estimation," Journal of Transport Geography, Elsevier, vol. 45(C), pages 32-47.
    2. Chu, Chi-Yang & Henderson, Daniel J. & Parmeter, Christopher F., 2017. "On discrete Epanechnikov kernel functions," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 79-105.
    3. Michael Noble & Helen Barnes & Gemma Wright & Benjamin Roberts, 2010. "Small Area Indices of Multiple Deprivation in South Africa," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 95(2), pages 281-297, January.
    4. Yuan Meng & Dongyang Hou & Hanfa Xing, 2017. "Rapid Detection of Land Cover Changes Using Crowdsourced Geographic Information: A Case Study of Beijing, China," Sustainability, MDPI, vol. 9(9), pages 1-16, August.
    5. Yu Liu & Xi Liu & Song Gao & Li Gong & Chaogui Kang & Ye Zhi & Guanghua Chi & Li Shi, 2015. "Social Sensing: A New Approach to Understanding Our Socioeconomic Environments," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 105(3), pages 512-530, May.
    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. Miaoxi Zhao & Gaofeng Xu & Martin de Jong & Xinjian Li & Pingcheng Zhang, 2020. "Examining the Density and Diversity of Human Activity in the Built Environment: The Case of the Pearl River Delta, China," Sustainability, MDPI, vol. 12(9), pages 1-21, May.

    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. Xiaosi Zhang & Jizhong Shao, 2024. "Evaluation of the Suitability of Street Vending Planning in Urban Public Space in the Post-COVID-19 Era," Land, MDPI, vol. 13(4), pages 1-26, April.
    2. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    3. Helai Huang & Jialing Wu & Fang Liu & Yiwei Wang, 2020. "Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data," Sustainability, MDPI, vol. 13(1), pages 1-23, December.
    4. Shi, Yishao & Tao, Tianhui & Cao, Xiangyang & Pei, Xiaowen, 2021. "The association between spatial attributes and neighborhood characteristics based on Meituan take-out data: Evidence from shanghai business circles," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    5. Arden Finn & Murray Leibbrandt & Ingrid Woolard, 2013. "What happened to multidimensional poverty in South Africa between 1993 and 2010?," SALDRU Working Papers 099, Southern Africa Labour and Development Research Unit, University of Cape Town.
    6. Li, Xin & Xie, Qianqian & Jiang, Jiaojiao & Zhou, Yuan & Huang, Lucheng, 2019. "Identifying and monitoring the development trends of emerging technologies using patent analysis and Twitter data mining: The case of perovskite solar cell technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 687-705.
    7. Chaogui Kang & Dongwan Fan & Hongzan Jiao, 2021. "Validating activity, time, and space diversity as essential components of urban vitality," Environment and Planning B, , vol. 48(5), pages 1180-1197, June.
    8. Xuewei Wang & Shuangli Ding & Weidong Cao & Dalong Fan & Bin Tang, 2020. "Research on Network Patterns and Influencing Factors of Population Flow and Migration in the Yangtze River Delta Urban Agglomeration, China," Sustainability, MDPI, vol. 12(17), pages 1-19, August.
    9. Yang, Xiping & Fang, Zhixiang & Xu, Yang & Yin, Ling & Li, Junyi & Lu, Shiwei, 2019. "Spatial heterogeneity in spatial interaction of human movements—Insights from large-scale mobile positioning data," Journal of Transport Geography, Elsevier, vol. 78(C), pages 29-40.
    10. Paulina Guerrero & Maja Steen Møller & Anton Stahl Olafsson & Bernhard Snizek, 2016. "Revealing Cultural Ecosystem Services through Instagram Images: The Potential of Social Media Volunteered Geographic Information for Urban Green Infrastructure Planning and Governance," Urban Planning, Cogitatio Press, vol. 1(2), pages 1-17.
    11. Ting Liu & Gang Cheng & Jie Yang, 2023. "Multi-Scale Recursive Identification of Urban Functional Areas Based on Multi-Source Data," Sustainability, MDPI, vol. 15(18), pages 1-24, September.
    12. Werner Liebregts & Pourya Darnihamedani & Eric Postma & Martin Atzmueller, 2020. "The promise of social signal processing for research on decision-making in entrepreneurial contexts," Small Business Economics, Springer, vol. 55(3), pages 589-605, October.
    13. Qian Chen & Tingting Ye & Naizhuo Zhao & Mingjun Ding & Zutao Ouyang & Peng Jia & Wenze Yue & Xuchao Yang, 2021. "Mapping China’s regional economic activity by integrating points-of-interest and remote sensing data with random forest," Environment and Planning B, , vol. 48(7), pages 1876-1894, September.
    14. Sadia Afrose & Ahmad Mojtoba Riyadh & Afsana Haque, 2019. "Cores of Dhaka city: area delimitation and comparison of their characteristics," Asia-Pacific Journal of Regional Science, Springer, vol. 3(2), pages 521-560, June.
    15. Amjad Ali & Marc Audi & Ismail Senturk & Yannick Roussel, 2022. "Do Sectoral Growth Promote CO2 Emissions in Pakistan? Time Series Analysis in Presence of Structural Break," International Journal of Energy Economics and Policy, Econjournals, vol. 12(2), pages 410-425, March.
    16. Bidur Devkota & Hiroyuki Miyazaki & Apichon Witayangkurn & Sohee Minsun Kim, 2019. "Using Volunteered Geographic Information and Nighttime Light Remote Sensing Data to Identify Tourism Areas of Interest," Sustainability, MDPI, vol. 11(17), pages 1-29, August.
    17. Yunzi Yang & Yuanyuan Ma & Hongzan Jiao, 2021. "Exploring the Correlation between Block Vitality and Block Environment Based on Multisource Big Data: Taking Wuhan City as an Example," Land, MDPI, vol. 10(9), pages 1-23, September.
    18. Guohua Feng & Jiti Gao & Xiaohui Zhang, 2018. "Estimation of technical change and price elasticities: a categorical time–varying coefficient approach," Journal of Productivity Analysis, Springer, vol. 50(3), pages 117-138, December.
    19. Yang Song & Kevin R. Gurney, 2020. "The Relationship between On-Road FFCO 2 Emissions and Socio-Economic/Urban Form Factors for Global Cities: Significance, Robustness and Implications," Sustainability, MDPI, vol. 12(15), pages 1-24, July.
    20. Wei Gao & Xiaoli Sun & Mei Zhao & Yong Gao & Haoran Ding, 2024. "Evaluate Human Perception of the Built Environment in the Metro Station Area," Land, MDPI, vol. 13(1), pages 1-25, January.

    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:jsusta:v:11:y:2019:i:17:p:4624-:d:260906. 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.