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

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  • 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
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    References listed on IDEAS

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    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.

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