IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i6p4896-d1093386.html
   My bibliography  Save this article

Identification of Emerging Roadkill Hotspots on Korean Expressways Using Space–Time Cubes

Author

Listed:
  • Minkyung Kim

    (Department of Environmental Science and Engineering, Ewha Womans University, Seoul 03760, Republic of Korea)

  • Sangdon Lee

    (Department of Environmental Science and Engineering, Ewha Womans University, Seoul 03760, Republic of Korea)

Abstract

Collisions with wild animals on high-speed expressways not only lead to roadkill but can also cause accidents that incur considerable human and economic costs. Based on roadkill data from 2004–2019 for four common wildlife species involved in collisions with vehicles on expressways in Korea (water deer, common raccoon dog, Korean hare, and wild boar), the present study conducted optimized hotspot analysis and identified spatiotemporal patterns using a space–time cube (STC) approach. Temporal and spatial differences in the roadkill data were observed between species. Water deer were the most common roadkill species of the four studied, with hotspots in the southern region of the capital area, in the Chungnam region, and in the western Chungbuk and Gangwon-do regions. However, the instances of water deer roadkill over time differed between each region. In addition, it was found that the number of cases of wild boar roadkill has increased recently. In particular, a number of new hotspot areas were observed centered on the metropolitan area Gyeonggi-do, which contains a high population and significant infrastructure. Overall, the emerging hotspot analysis based on STCs was able to determine cold spot and hotspot trends over time, allowing for a more intuitive understanding of spatiotemporal clustering patterns and associated changes than cumulative density-oriented hotspot analysis. As a result, it becomes easier to analyze the causes of roadkill and to establish reduction measures according to priority.

Suggested Citation

  • Minkyung Kim & Sangdon Lee, 2023. "Identification of Emerging Roadkill Hotspots on Korean Expressways Using Space–Time Cubes," IJERPH, MDPI, vol. 20(6), pages 1-12, March.
  • Handle: RePEc:gam:jijerp:v:20:y:2023:i:6:p:4896-:d:1093386
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/6/4896/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/20/6/4896/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yajie Zou & Xinzhi Zhong & Jinjun Tang & Xin Ye & Lingtao Wu & Muhammad Ijaz & Yinhai Wang, 2019. "A Copula-Based Approach for Accommodating the Underreporting Effect in Wildlife‒Vehicle Crash Analysis," Sustainability, MDPI, vol. 11(2), pages 1-13, January.
    2. Hyomin Park & Minkyung Kim & Sangdon Lee, 2021. "Spatial Characteristics of Wildlife-Vehicle Collisions of Water Deer in Korea Expressway," Sustainability, MDPI, vol. 13(24), pages 1-13, December.
    Full references (including those not matched with items on IDEAS)

    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. Jingjing Xu & Behram Wali & Xiaobing Li & Jiaqi Yang, 2019. "Injury Severity and Contributing Driver Actions in Passenger Vehicle–Truck Collisions," IJERPH, MDPI, vol. 16(19), pages 1-16, September.
    2. Qian Duan & Xin Ye & Jian Li & Ke Wang, 2020. "Empirical Modeling Analysis of Potential Commute Demand for Carsharing in Shanghai, China," Sustainability, MDPI, vol. 12(2), pages 1-18, January.
    3. Butts, David J. & Thompson, Noelle E. & Christensen, Sonja A. & Williams, David M. & Murillo, Michael S., 2022. "Data-driven agent-based model building for animal movement through Exploratory Data Analysis," Ecological Modelling, Elsevier, vol. 470(C).
    4. Ruone Zhang & Xin Ye & Ke Wang & Dongjin Li & Jiayu Zhu, 2019. "Development of Commute Mode Choice Model by Integrating Actively and Passively Collected Travel Data," Sustainability, MDPI, vol. 11(10), pages 1-15, May.
    5. Yan, Ying & Zhang, Ying & Yang, Xiangli & Hu, Jin & Tang, Jinjun & Guo, Zhongyin, 2020. "Crash prediction based on random effect negative binomial model considering data heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    6. Andrius Kučas & Linas Balčiauskas & Carlo Lavalle, 2023. "Identification of Urban and Wildlife Terrestrial Corridor Intersections for Planning of Wildlife-Vehicle Collision Mitigation Measures," Land, MDPI, vol. 12(4), pages 1-18, March.
    7. Sungwon Hong & Hee-Bok Park & Mihyun Kim & Hyo Gyeom Kim, 2022. "History and Future Challenges of Roadkill Research in South Korea," Sustainability, MDPI, vol. 14(23), pages 1-12, November.
    8. Xin Guan & Xin Ye & Cheng Shi & Yajie Zou, 2019. "A Multivariate Modeling Analysis of Commuters’ Non-Work Activity Allocations in Xiaoshan District of Hangzhou, China," Sustainability, MDPI, vol. 11(20), pages 1-19, October.
    9. Luo, Qiang & Yuan, Jie & Chen, Xinqiang & Wu, Shubo & Qu, Zhijian & Tang, Jinjun, 2019. "Analyzing start-up time headway distribution characteristics at signalized intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    10. Yanni Liang & Jianxin You & Ran Wang & Bo Qin & Shuo Han, 2024. "Urban Transportation Data Research Overview: A Bibliometric Analysis Based on CiteSpace," Sustainability, MDPI, vol. 16(22), pages 1-45, November.
    11. Jibiao Zhou & Xinhua Mao & Yiting Wang & Minjie Zhang & Sheng Dong, 2019. "Risk Assessment in Urban Large-Scale Public Spaces Using Dempster-Shafer Theory: An Empirical Study in Ningbo, China," IJERPH, MDPI, vol. 16(16), pages 1-28, August.

    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:jijerp:v:20:y:2023:i:6:p:4896-:d:1093386. 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.