IDEAS home Printed from https://ideas.repec.org/a/eur/ejfejr/25.html
   My bibliography  Save this article

An Evaluation of Urban Open Spaces in Larisa, Greece

Author

Listed:
  • Charalampos Kyriakidis

    (Ph.D. Candidate, Urban - Regional Planner, Transportation Engineer, Sustainable Mobility Unit- Department of Geography - Regional Planning, National Technical University of Athens)

Abstract

A great deal of researchers elaborated on the importance of the urban spaces and human life. Urban spaces are necessary types of spaces for a city and they have a timeless value. This research is focused on people’s perception about urban spaces in Larisa, Greece, a medium-sized city selected as case study. An electronic questionnaire survey was conducted and conclusions are drawn on how adequate are the urban spaces in Larisa. Moreover, people are asked to propose ideas on how other spaces, function more as urban gaps, can be integrated on the urban grid. In that way, it is easy to study what people believe about the city’s life and how the existing urban spaces function. Some conclusions derived from this research can be also useful in succeeding a combined traffic and urban planning in other Greek, in the context of the implementation of a Sustainable Urban Mobility Plan (SUMP).

Suggested Citation

  • Charalampos Kyriakidis, 2021. "An Evaluation of Urban Open Spaces in Larisa, Greece," European Journal of Formal Sciences and Engineering Articles, Revistia Research and Publishing, vol. 4, January -.
    • Handle: RePEc:eur:ejfejr:25
    as

    Download full text from publisher

    File URL: https://revistia.com/index.php/ejfe/article/view/1792
    Download Restriction: no
    File URL: https://revistia.com/files/articles/ejfe_v4_i1_21/Kyriakidis.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Thin-Yin Leong, 2007. "Simpler Spreadsheet Simulation of Multi-Server Queues," INFORMS Transactions on Education, INFORMS, vol. 7(2), pages 172-177, January.
    2. Thin-Yin Leong, 2007. "Monte Carlo Spreadsheet Simulation Using Resampling," INFORMS Transactions on Education, INFORMS, vol. 7(3), pages 188-200, May.
    3. David Kendrick, 2007. "Teaching Computational Economics to Graduate Students," Computational Economics, Springer;Society for Computational Economics, vol. 30(4), pages 381-391, November.
    4. Lu, Xiaoling & Dong, Fengchi & Liu, Xiexin & Chang, Xiangyu, 2018. "Varying Coefficient Support Vector Machines," Statistics & Probability Letters, Elsevier, vol. 132(C), pages 107-115.
    5. Thin-Yin Leong & Michelle L. F. Cheong, 2008. "Teaching Business Modeling Using Spreadsheets," INFORMS Transactions on Education, INFORMS, vol. 9(1), pages 20-34, September.
    6. Xiao-Sheng Si & Zheng-Xin Zhang & Chang-Hua Hu, 2017. "Advances in Data-Driven RUL Prognosis Techniques," Springer Series in Reliability Engineering, in: Data-Driven Remaining Useful Life Prognosis Techniques, chapter 0, pages 3-21, Springer.
    7. repec:zib:zjmerd:3jmerd2018-102-105 is not listed on IDEAS
    8. Tan, P. & Jiang, H.R. & Zhu, X.B. & An, L. & Jung, C.Y. & Wu, M.C. & Shi, L. & Shyy, W. & Zhao, T.S., 2017. "Advances and challenges in lithium-air batteries," Applied Energy, Elsevier, vol. 204(C), pages 780-806.
    9. Willcock, Simon & Martínez-López, Javier & Hooftman, Danny A.P. & Bagstad, Kenneth J. & Balbi, Stefano & Marzo, Alessia & Prato, Carlo & Sciandrello, Saverio & Signorello, Giovanni & Voigt, Brian & Vi, 2018. "Machine learning for ecosystem services," Ecosystem Services, Elsevier, vol. 33(PB), pages 165-174.
    10. Krapf, Brandy & Raab, Dwight & Zwilling, Bradley, 2018. "Machinery Values on Illinois Grain Farms," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 8, 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. Leong Thin-Yin & Leong Yonghui Jonathan, 2020. "Simpler Machine Learning Using Spreadsheets: Neural Network Predict," European Journal of Engineering and Formal Sciences Articles, European Center for Science Education and Research, vol. 4, January -.
    2. Yi-Jhen Wu & Yi-Hsin Chen & Sarah M. Kiefer & Claus H. Carstensen, 2021. "Learning Strategies as Moderators Between Motivation and Mathematics Performance in East Asian Students: Latent Class Analysis," SAGE Open, , vol. 11(4), pages 21582440211, November.
    3. Dae-Seon Hong & Yeon-Ji Choi & Chang-Su Jin & Kyoung-Hee Shin & Woo-Jin Song & Sun-Hwa Yeon, 2023. "Enhanced Cycle Performance of NiCo 2 O 4 /CNTs Composites in Lithium-Air Batteries," Energies, MDPI, vol. 17(1), pages 1-14, December.
    4. Huang, Qisheng & Xu, Yunjian & Courcoubetis, Costas, 2020. "Stackelberg competition between merchant and regulated storage investment in wholesale electricity markets," Applied Energy, Elsevier, vol. 264(C).
    5. Mark W. Isken, 2014. "Translating a Lab Based Spreadsheet Modeling Course to an Online Format: Experience from a Natural Experiment," INFORMS Transactions on Education, INFORMS, vol. 14(3), pages 120-128, May.
    6. Hsieh, I-Yun Lisa & Pan, Menghsuan Sam & Chiang, Yet-Ming & Green, William H., 2019. "Learning only buys you so much: Practical limits on battery price reduction," Applied Energy, Elsevier, vol. 239(C), pages 218-224.
    7. Agudelo, César Augusto Ruiz & Bustos, Sandra Liliana Hurtado & Moreno, Carmen Alicia Parrado, 2020. "Modeling interactions among multiple ecosystem services. A critical review," Ecological Modelling, Elsevier, vol. 429(C).
    8. Wang, Yuanhui & Hao, Liang & Bai, Minli, 2022. "Modeling the multi-step discharge and charge reaction mechanisms of non-aqueous Li-O2 batteries," Applied Energy, Elsevier, vol. 317(C).
    9. Freitas Gomes, Icaro Silvestre & Perez, Yannick & Suomalainen, Emilia, 2020. "Coupling small batteries and PV generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 126(C).
    10. Duffner, Fabian & Mauler, Lukas & Wentker, Marc & Leker, Jens & Winter, Martin, 2021. "Large-scale automotive battery cell manufacturing: Analyzing strategic and operational effects on manufacturing costs," International Journal of Production Economics, Elsevier, vol. 232(C).
    11. Signorello, Giovanni & Prato, Carlo & Marzo, Alessia & Ientile, Renzo & Cucuzza, Giuseppe & Sciandrello, Saverio & Martínez-López, Javier & Balbi, Stefano & Villa, Ferdinando, 2018. "Are protected areas covering important biodiversity sites? An assessment of the nature protection network in Sicily (Italy)," Land Use Policy, Elsevier, vol. 78(C), pages 593-602.
    12. Richards, Daniel Rex & Lavorel, Sandra, 2022. "Integrating social media data and machine learning to analyse scenarios of landscape appreciation," Ecosystem Services, Elsevier, vol. 55(C).
    13. Manley, Kyle & Nyelele, Charity & Egoh, Benis N., 2022. "A review of machine learning and big data applications in addressing ecosystem service research gaps," Ecosystem Services, Elsevier, vol. 57(C).
    14. LeBlanc, Larry J. & Grossman, Thomas A. & Bartolacci, Michael R., 2019. "Ensuring scalability and reusability of spreadsheet linear programming models," Omega, Elsevier, vol. 84(C), pages 55-69.
    15. Xinchen Gu & Aihua Long & Guihua Liu & Jiawen Yu & Hao Wang & Yongmin Yang & Pei Zhang, 2021. "Changes in Ecosystem Service Value in the 1 km Lakeshore Zone of Poyang Lake from 1980 to 2020," Land, MDPI, vol. 10(9), pages 1-19, September.
    16. Bagstad, Kenneth J. & Ingram, Jane Carter & Shapiro, Carl D. & La Notte, Alessandra & Maes, Joachim & Vallecillo, Sara & Casey, C. Frank & Glynn, Pierre D. & Heris, Mehdi P. & Johnson, Justin A. & Lau, 2021. "Lessons learned from development of natural capital accounts in the United States and European Union," Ecosystem Services, Elsevier, vol. 52(C).
    17. Huang, Zhiliang & Wang, Huaixing & Gan, Zhouwang & Yang, Tongguang & Yuan, Cong & Lei, Bing & Chen, Jie & Wu, Shengben, 2024. "An mechanical/thermal analytical model for prismatic lithium-ion cells with silicon‑carbon electrodes in charge/discharge cycles," Applied Energy, Elsevier, vol. 365(C).
    18. Sarah G. Nurre & Jeffery D. Weir, 2017. "Interactive Excel-Based Gantt Chart Schedule Builder," INFORMS Transactions on Education, INFORMS, vol. 17(2), pages 49-57, January.
    19. Tan, Peng & Xiao, Xu & Dai, Yawen & Cheng, Chun & Ni, Meng, 2020. "Photo-assisted non-aqueous lithium-oxygen batteries: Progress and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    20. Junyi Wu & Shari Shang, 2020. "Managing Uncertainty in AI-Enabled Decision Making and Achieving Sustainability," Sustainability, MDPI, vol. 12(21), pages 1-17, October.

    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:eur:ejfejr:25. 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: Revistia Research and Publishing (email available below). General contact details of provider: https://revistia.com/index.php/ejfe .

    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.