IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i3p377-d1358321.html
   My bibliography  Save this article

Bridging Geospatial and Semantic Worlds: Enhancing Analysis of Place-Based Concepts in GIS

Author

Listed:
  • Omid Reza Abbasi

    (Department of Geospatial Information Systems, K. N. Toosi University of Technology, Tehran 19967-15433, Iran)

  • Ali Asghar Alesheikh

    (Department of Geospatial Information Systems, K. N. Toosi University of Technology, Tehran 19967-15433, Iran)

  • Aynaz Lotfata

    (Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, CA 90616, USA)

  • Chiara Garau

    (Department of Civil, Environmental Engineering, and Architecture (DICAAR), University of Cagliari, 09124 Cagliari, Italy)

Abstract

People’s actions and behaviours contribute to the diversity and personality of a space, transforming it into a vibrant and thriving living environment. The main goal of this research is to present a GIS-based framework for assessing places. The framework is constructed based on the idea of conceptual spaces, integrating spatial and semantic concepts inside a geometric structure. The explanation of place-related concepts is achieved via the use of linear programming and convex polytopes. By projecting these concepts into the spatial domain, a strong connection between geographical and semantic space is established. This connection allows a wide range of analytical calculations using geographic information systems to be carried out. The study focuses on the sense of city centre in Tehran, Iran, by employing questionnaires administrated on-site to evaluate the correlation between identified city centres and the participants’ responses. The findings demonstrate a good correlation, as shown by a Pearson correlation value of 0.74 and a rank correlation coefficient of 0.8. Interestingly, the city centres that were selected did not always align with the geographic centre. However, participants still perceived them as city centres. This framework serves as a valuable tool for planners and policymakers, providing a comprehensive understanding of the built environment. By considering both semantic and geographical aspects, the framework emphasises the importance of emotions, memories, and meanings in creating an inclusive environment.

Suggested Citation

  • Omid Reza Abbasi & Ali Asghar Alesheikh & Aynaz Lotfata & Chiara Garau, 2024. "Bridging Geospatial and Semantic Worlds: Enhancing Analysis of Place-Based Concepts in GIS," Land, MDPI, vol. 13(3), pages 1-22, March.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:3:p:377-:d:1358321
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/3/377/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/13/3/377/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Crone, Sven F. & Lessmann, Stefan & Stahlbock, Robert, 2006. "The impact of preprocessing on data mining: An evaluation of classifier sensitivity in direct marketing," European Journal of Operational Research, Elsevier, vol. 173(3), pages 781-800, September.
    2. Alireza Taravat & Masih Rajaei & Iraj Emadodin, 2017. "Urbanization dynamics of Tehran city (1975–2015) using artificial neural networks," Journal of Maps, Taylor & Francis Journals, vol. 13(1), pages 24-30, January.
    3. Matthew Browning & Kangjae Lee, 2017. "Within What Distance Does “Greenness” Best Predict Physical Health? A Systematic Review of Articles with GIS Buffer Analyses across the Lifespan," IJERPH, MDPI, vol. 14(7), pages 1-21, June.
    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. Nabetse Baruc Blas-Miranda & Ana Lilia Lozada-Tequeanes & Juan Antonio Miranda-Zuñiga & Marcia P. Jimenez, 2022. "Green Space Exposure and Obesity in the Mexican Adult Population," IJERPH, MDPI, vol. 19(22), pages 1-13, November.
    2. Hao-Ting Chang & Chih-Da Wu & Wen-Chi Pan & Shih-Chun Candice Lung & Huey-Jen Su, 2019. "Association Between Surrounding Greenness and Schizophrenia: A Taiwanese Cohort Study," IJERPH, MDPI, vol. 16(8), pages 1-16, April.
    3. Matthew H. E. M. Browning & Alessandro Rigolon, 2019. "School Green Space and Its Impact on Academic Performance: A Systematic Literature Review," IJERPH, MDPI, vol. 16(3), pages 1-22, February.
    4. Lee, In Gyu & Yoon, Sang Won & Won, Daehan, 2022. "A Mixed Integer Linear Programming Support Vector Machine for Cost-Effective Group Feature Selection: Branch-Cut-and-Price Approach," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1055-1068.
    5. Crone, Sven F. & Finlay, Steven, 2012. "Instance sampling in credit scoring: An empirical study of sample size and balancing," International Journal of Forecasting, Elsevier, vol. 28(1), pages 224-238.
    6. Georgios Marinakos & Sophia Daskalaki, 2017. "Imbalanced customer classification for bank direct marketing," Journal of Marketing Analytics, Palgrave Macmillan, vol. 5(1), pages 14-30, March.
    7. Coussement, Kristof & De Bock, Koen W., 2013. "Customer churn prediction in the online gambling industry: The beneficial effect of ensemble learning," Journal of Business Research, Elsevier, vol. 66(9), pages 1629-1636.
    8. Brandner, Hubertus & Lessmann, Stefan & Voß, Stefan, 2013. "A memetic approach to construct transductive discrete support vector machines," European Journal of Operational Research, Elsevier, vol. 230(3), pages 581-595.
    9. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
    10. Alessandro Rigolon & Matthew H. E. M. Browning & Olivia McAnirlin & Hyunseo (Violet) Yoon, 2021. "Green Space and Health Equity: A Systematic Review on the Potential of Green Space to Reduce Health Disparities," IJERPH, MDPI, vol. 18(5), pages 1-27, March.
    11. Lessmann, Stefan & Baesens, Bart & Seow, Hsin-Vonn & Thomas, Lyn C., 2015. "Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research," European Journal of Operational Research, Elsevier, vol. 247(1), pages 124-136.
    12. Coussement, Kristof & Van den Bossche, Filip A.M. & De Bock, Koen W., 2014. "Data accuracy's impact on segmentation performance: Benchmarking RFM analysis, logistic regression, and decision trees," Journal of Business Research, Elsevier, vol. 67(1), pages 2751-2758.
    13. Obinna Justice Ubani & Micheal Oloyede Alabi & Emmanuel Ndukwe Chiemelu & Andrew Okosun & Chinwe Sam-Amobi, 2023. "Influence of Spatial Accessibility and Environmental Quality on Youths’ Visit to Green Open Spaces (GOS) in Akure, Nigeria," Sustainability, MDPI, vol. 15(17), pages 1-21, September.
    14. Andreia Teixeira & Ronaldo Gabriel & José Martinho & Irene Oliveira & Mário Santos & Graça Pinto & Helena Moreira, 2023. "Distance to Natural Environments, Physical Activity, Sleep, and Body Composition in Women: An Exploratory Analysis," IJERPH, MDPI, vol. 20(4), pages 1-20, February.
    15. Yijun Zhang & Suzanne Mavoa & Jinfeng Zhao & Deborah Raphael & Melody Smith, 2020. "The Association between Green Space and Adolescents’ Mental Well-Being: A Systematic Review," IJERPH, MDPI, vol. 17(18), pages 1-26, September.
    16. K. W. De Bock & D. Van Den Poel, 2012. "Reconciling Performance and Interpretability in Customer Churn Prediction using Ensemble Learning based on Generalized Additive Models," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/805, Ghent University, Faculty of Economics and Business Administration.
    17. Jake M. Robinson & Anna Jorgensen & Ross Cameron & Paul Brindley, 2020. "Let Nature Be Thy Medicine: A Socioecological Exploration of Green Prescribing in the UK," IJERPH, MDPI, vol. 17(10), pages 1-24, May.
    18. Jue Wang & Mei-Po Kwan, 2018. "An Analytical Framework for Integrating the Spatiotemporal Dynamics of Environmental Context and Individual Mobility in Exposure Assessment: A Study on the Relationship between Food Environment Exposu," IJERPH, MDPI, vol. 15(9), pages 1-24, September.
    19. Bose, Indranil & Chen, Xi, 2009. "Quantitative models for direct marketing: A review from systems perspective," European Journal of Operational Research, Elsevier, vol. 195(1), pages 1-16, May.
    20. Siyu Ma & Lin Yang & Mei-Po Kwan & Zejun Zuo & Haoyue Qian & Minghao Li, 2021. "Do Individuals’ Activity Structures Influence Their PM 2 . 5 Exposure Levels? Evidence from Human Trajectory Data in Wuhan City," IJERPH, MDPI, vol. 18(9), pages 1-27, April.

    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:13:y:2024:i:3:p:377-:d:1358321. 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.