GIS-Based Car Parking Suitability Analysis in Sustainable Transportation Planning

Year 2024, Volume: 24 Issue: 3, 628 - 640, 27.06.2024

Arif Çağdaş Aydınoğlu , Süleyman Şişman , Mesube Azize Şaşmaz , Selin Nur Akın

https://doi.org/10.35414/akufemubid.1332755

Abstract

Recently, changes in working life and daily lifestyles have caused more people to move to cities. The increasing population brought the rapid increase in the number of vehicles in parallel and negatively affected the urban transportation systems. Therefore, problems occur due to the lack of car parking areas, which are of great importance in sustainable urban transportation, and their planning in unsuitable locations. Considering that cars spend most of their time in car parking areas known as static traffic, traffic congestion and mobility of cars are optimized by determining suitable parking locations. This situation is of great importance in terms of car ownership and ensuring fluently transportation in metropolitan areas where the population per unit area is high. In this study, 23 criteria were determined in the criteria groups of Transportation, Economy & Finance and Potential Attraction Properties for sustainable transportation planning in the car parking suitability analysis. For criterion weights, a survey was conducted with participation of relevant sector stakeholders. The surveys were analyzed using the Best Worst Method (BWM) technique, one of the Multi Criteria Decision Analysis (MCDA) techniques, and criterion weights were calculated. Pendik and Tuzla districts of Istanbul and Gebze, Çayırova and Darıca districts of Kocaeli were determined as the study area, and data representing criteria were obtained in the study area. Geographic Information Systems (GIS)-based suitability analysis was performed by evaluating data with geographical analysis techniques such as proximity, slope, fuzzy logic and weighted overlay. Thus, a total of 18.38 km2 in 5 different locations in Pendik, a total of 8.55 km2 in 4 different locations in Tuzla and 6.51 km2 in Gebze were determined as zonal suitable areas. The results can be considered as effective decision support mechanism for locating parking areas in suitable locations in cities. Car parking areas planned in suitable locations can contribute to improving the quality of urban life by reducing traffic congestion and carbon emissions released into environment.

Keywords

Best Worst Method (BWM);, Geographic Information Systems, Fuzzy Logic, ; Car Parking Suitability Analysis

Sürdürülebilir Ulaşım Planlamasında CBS Tabanlı Otopark Uygunluk Analizi

Abstract

Son zamanlarda çalışma hayatı ve günlük yaşam biçimlerindeki değişimler daha fazla insanın şehirlere yönelmesine neden olmuştur. Artan nüfus, araç sayısındaki hızlı artışı da paralelinde getirmiş olup şehir içi ulaşım sistemlerini olumsuz etkilemiştir. Bu yüzden sürdürülebilir kentsel ulaşımda büyük öneme sahip otoparkların eksik olması ve uygun olmayan konumlara planlanmasından dolayı problemler meydana gelmektedir. Araçların durağan trafik olarak bilinen otoparklarda zamanının çoğunu geçirdiği göz önüne alındığında, uygun otopark konumların belirlenmesi ile trafik sıkışıklığı ve araçların hareket kabiliyeti optimize edilmektedir. Araç sahipliği ve birim alandaki nüfusun fazla olduğu metropoliten alanlarda ulaşımın sorunsuz sağlanması açısından bu durum büyük öneme sahiptir. Bu çalışmada sürdürülebilir ulaşım planlamasın için otopark uygunluk analizinde Ulaşım, Ekonomi&Finans ve Potansiyel Çekim Özellikleri kriter gruplarında 23 kriter belirlenmiştir. Kriter ağırlıkları için ilgili sektör paydaşlarının katıldığı anket çalışması gerçekleştirilmiştir. Anketler Çok Kriterli Karar Verme (ÇKKV) tekniklerinden En İyi-En Kötü (Best Worst Method-BWM) tekniği ile analiz edilmiş olup, kriter ağırlıkları hesaplanmıştır. İstanbul’un Pendik ve Tuzla ilçeleri ile Kocaeli’nin Gebze, Çayırova ve Darıca ilçeleri çalışma alanı olarak belirlenmiş olup, çalışma alanında kriterlere ilişkin veriler elde edilmiştir. Veriler yakınlık, eğim, bulanık mantık ve ağırlıklı bindirme gibi coğrafi analiz teknikleri ile değerlendirilerek Coğrafi Bilgi Sistemleri (CBS) tabanlı uygunluk analizi gerçekleştirilmiştir. Böylelikle Pendik ilçesinde 5 farklı konumda toplam 18.38 km2, Tuzla ilçesinde 4 farklı konumda toplam 8.55 km2 ve Gebze ilçesinde 6.51 km2 bölgesel uygun alanlar tespit edilmiştir. Sonuçlar kentlerde otoparkların uygun yerlere konumlandırılmasında etkin karar-destek mekanizması olarak değerlendirilebilir. Uygun yerlere planlanmış otoparklar trafik sıkışıklığı ve çevreye salınan karbon emisyonlarının azaltılmasıyla kentsel yaşam kalitesinin artırılmasına katkı sağlayabilir.

Keywords

En İyi-En Kötü Yöntemi(BWM), Coğrafi Bilgi Sistemleri, Bulanık Mantık, Otopark Uygunluk Analizi

Thanks

Bu çalışma kapsamında kullanılan coğrafi verilerin temini konusunda Kocaeli Büyükşehir Belediyesi (KBB) Bilgi İşlem Dairesi Başkanlığı, Akıllı Şehirler ve Kent Bilgi Sistemleri Şube Müdürlüğü’ne, İstanbul Büyükşehir Belediyesi (İBB) Ulaşım Daire Başkanlığı, Ulaşım Planlama Müdürlüğü’ne ve anketlere katılım sağlayan İSPARK İstanbul Otopark İşletmeleri Tic. AŞ çalışanlarına teşekkürlerimizi sunarız.

References

• Akyuz, G., Yalpir, Ş., Ertunc, E., 2023. Determining the Suitability of Lands for Agricultural Use with the Best-Worst Method. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, 23(4), 1045-1055. https://doi.org/10.35414/akufemubid.1229833
• Aliniai, K., Yarahmadi, A., Zarin, J. Z., Yarahmadi, H. and Lak, S. B., 2015. Parking lot site selection: An opening gate towards sustainable GIS-based urban traffic management, Journal of the Indian Society of Remote Sensing, 43, 801-813. https://doi.org/10.1007/s12524-014-0415-3
• Ari, Y. 2022. A Statistical Approach to Urbanization: The Case of Turkey. In Promoting Statistical Practice and Collaboration in Developing Countries (pp. 431-445). Chapman and Hall/CRC.
• Aydinoglu, A. C. and Iqbal, A. S., 2021. Determining parking demand and locating parking areas using geographic analytics methods, Journal of Urban Planning and Development, 147(1), 05020035. https://doi.org/10.1061/(ASCE)UP.1943-5444.000065
• Babaei, A., Khedmati, M., Jokar, M. R. A., Tirkolaee, E. B., 2023. Sustainable transportation planning considering traffic congestion and uncertain conditions. Expert Systems with Applications, 227, 119792. https://doi.org/10.1016/j.eswa.2023.119792
• Bibri, S. E. and Krogstie, J., 2017. The core enabling technologies of big data analytics and context-aware computing for smart sustainable cities: a review and synthesis, Journal of Big Data, 4, 1-50. https://doi.org/10.1186/s40537-017-0091-6
• Bovkir, R., Aydinoglu, A.C., 2018. Providing land value information from geographic data infrastructure by using fuzzy logic analysis approach. Land use policy, 78, 46-60. https://doi.org/10.1016/j.landusepol.2018.06.040
• Bovkir, R., Ustaoglu, E., Aydinoglu, A.C., 2023. Assessment of Urban Quality of Life Index at Local Scale with Different Weighting Approaches. Social Indicators Research, 165(2), 655-678. https://doi.org/10.1007/s11205-022-03036-y
• D'Alpaos, C. and Andreolli, F., 2020. Urban quality in the city of the future: A bibliometric multicriteria assessment model, Ecological Indicators, 117, 106575. https://doi.org/10.1016/j.ecolind.2020.106575
• Dehghani, A., Soltani, A., 2023. Site Selection of Car Parking With the GIS-Based Fuzzy Multi-Criteria Decision Making. International Journal of Information Technology & Decision Making, 1-26. https://doi.org/10.1142/S0219622023500293
• Demir, S., 2016. Use of the spatial multiple criteria decision making techniques in the selection of car parking area, Yüksek Lisans Tezi, Yıldız Teknik Üniversitesi Fen Bilimleri Enstitüsü, İstanbul, 106.
• Demir, S., Basaraner, M. and Gumus, A. T., 2021. Selection of suitable parking lot sites in megacities: A case study for four districts of Istanbul, Land use policy, 111, 105731. https://doi.org/10.1016/j.landusepol.2021.105731
• Farzanmanesh, R., Naeeni, A. G. and Abdullah, A. M., 2010. Parking site selection management using Fuzzy logic and Multi Criteria Decision Making, Environment Asia, 3(3), 109-116.
• Golias, J., Yannis, G. and Harvatis, M., 2002. Off-street parking choice sensitivity, Transportation Planning and Technology, 25(4), 333-348. https://doi.org/10.1080/0308106022000019620
• Hollands, R. G., 2008. Will the real smart city please stand up? Intelligent, progressive or entrepreneurial? City, 12(3), 303-320. https://doi.org/10.1080/13604810802479126
• Hosseinlou, M. H., Balal, E., Massahi, A. and Ghiasi, I., 2012. Developing optimal zones for urban parking spaces by Arc GIS and AHP, Indian Journal of Science and Technology, 5(11), 3618-3622.
• İSPARK, 2016. İstanbul Otopark Ana Planı. İstanbul Otopark İşletmeleri Tic. A.Ş (İSPARK), 1. Baskı, İstanbul.
• Jelokhani-Niaraki, M. and Malczewski, J., 2015. A group multicriteria spatial decision support system for parking site selection problem: A case study, Land Use Policy, 42, 492-508. https://doi.org/10.1016/j.landusepol.2014.09.003
• Karimi, V., Ebadi, H. and Ahmady, S., 2009. Modeling of parking site selection by using GIS with emphasis on weighting and integrating layers, Journal of Faculty of Eng, 38(3), 11-21.
• Kaufmann, A., Gupta, M.M., 1988. Fuzzy Mathematical Models in Engineering and Management Science. North-Holland, Amsterdam.
• Krasić, D. and Lanović, Z., 2013. Park & Ride facility planning, Građevinar, 65(2), 111-121.
• Levy, N., Benenson, I. 2015. GIS-based method for assessing city parking patterns. Journal of Transport Geography, 46, 220-231. https://doi.org/10.1016/j.jtrangeo.2015.06.015
• Li, L. B., Wang, M. and Wu, B., 2009. Study on the location parking index based on function division of parking space, In ICCTP 2009: Critical Issues In Transportation Systems Planning, Development and Management, 1-8. https://doi.org/10.1061/41064(358)176
• Mi, X., Tang, M., Liao, H., Shen, W., Lev, B., 2019. The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?. Omega, 87, 205-225. https://doi.org/10.1016/j.omega.2019.01.009
• Mohamed, A. A., Kronenberg, J., Łaszkiewicz, E., 2022. Transport infrastructure modifications and accessibility to public parks in Greater Cairo. Urban Forestry & Urban Greening, 73, 127599. https://doi.org/10.1016/j.ufug.2022.127599
• Neirotti, P., De Marco, A., Cagliano, A. C., Mangano, G. and Scorrano, F., 2014. Current trends in Smart City initiatives: Some stylised facts, Cities, 38, 25-36. https://doi.org/10.1016/j.cities.2013.12.010
• Ozturk, D. and Kılıç-Gul, F., 2020. GIS-based multi-criteria decision analysis for parking site selection, Kuwait Journal of Science, 47(3), 2-14.
• Palevičius, V., Paliulis, G. M., Venckauskaite, J. and Vengrys, B., 2013. Evaluation of the requirement for passenger car parking spaces using multi-criteria methods, Journal of Civil Engineering and Management, 19(1), 49-58. https://doi.org/10.3846/13923730.2012.727463
• Rezaei, J., 2015. Best-worst multi-criteria decision-making method, Omega, 53, 49-57. https://doi.org/10.1016/j.omega.2014.11.009
• Rezaei, J., 2016. Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126-130. https://doi.org/10.1016/j.omega.2015.12.001
• Saaty, T. L., 2008. Decision making with the analytic hierarchy process. International Journal Of Services Sciences, 1(1), 83-98. https://doi.org/10.1504/IJSSCI.2008.017590
• Sisman, S. and Aydinoglu, A. C., 2020. Using GIS-based multi-criteria decision analysis techniques in the smart cities. 5th International Conference on Smart City Applications. Karabük, Türkiye, 383-389.
• Toan, T.D., 2022. Smart Planning and Management Solutions for Smart Mobility. In CIGOS 2021, Emerging Technologies and Applications for Green Infrastructure: Proceedings of the 6th International Conference on Geotechnics, Civil Engineering and Structures, Springer Singapore. 1397-1405.
• Ustaoglu, E., Kabadayı, M.E., 2021. Reconstruction of Residential Land Cover and Spatial Analysis of Population in Bursa Region (Turkey) in the Mid-Nineteenth Century. Land, 10(10), 1077. https://doi.org/10.3390/land10101077
• Ustaoglu, E., Sisman, S., Aydınoglu, A.C., 2021. Determining agricultural suitable land in peri-urban geography using GIS and Multi Criteria Decision Analysis (MCDA) techniques. Ecological Modelling, 455, 109610. https://doi.org/10.1016/j.ecolmodel.2021.109610
• Yilmaz, C., Baykoc, O. F. 2022. A Decision Support System for Parking Lot Location Problems in Metropoles: A Case Study in Istanbul. In International Conference on Management Science and Engineering Management, Cham: Springer International Publishing, 124-135.
• Zadeh, L.A., 1965. Fuzzy sets. Information and Control, 8, 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
• Zhang, H., Chen, M., Liang, C. 2022. Urbanization of county in China: Spatial patterns and influencing factors. Journal of Geographical Sciences, 32(7), 1241-1260. https://doi.org/10.1007/s11442-022-1995-4
• Zimmermann, H.J., 2001. Fuzzy Set Theory and Its Applications, 4th edition. Springer, New York, 514 .
• GMR, 2022. Global Mobility Report 2022: Tracking Sector Performance (GMR). https://www.sum4all.org/data/files/global_mobility_report_2022_04052023_final.pdf, (06.12.2023)
• İBB Açık Veri Potalı, 2023. İstanbul Büyükşehir Belediyesi (İBB) Açık Veri Portalı. https://data.ibb.gov.tr/, (10.07.2023)
• İPA, 2023. Kent Gündemine Bakiş: İstanbul’da Sürdürülebilir Ulaşıma Doğru. İstanbul Planlama Ajansı (İPA). https://ipa.istanbul/yayinlarimiz/genel/istanbulda-surdurulebilir-ulasima-dogru/, (06.12.2023)
• OSM, 2023. Open Street Map (OSM). https://www.openstreetmap.org/, (10.07.2023)
• TÜİK, 2023. Türkiye İstatistik Kurumu (TÜİK). 2022 Yılı Kent-Kır Nüfus İstatistikleri. https://data.tuik.gov.tr/Bulten/Index?p=Kent-Kir-Nufus-Istatistikleri-2022-49755, (05.12.2023)
• TÜİK, 2023a. Türkiye İstatistik Kurumu (TÜİK). Nüfus ve Demografi İstatistikleri. https://data.tuik.gov.tr/Kategori/GetKategori?p=Nufus-ve-Demografi-109, (10.07.2023)
• TÜİK, 2023b. Türkiye İstatistik Kurumu (TÜİK). Ulaştırma ve Haberleşme İstatistikleri, İllere Göre Motorlu Kara Taşıtları Sayısı. https://data.tuik.gov.tr/Kategori/GetKategori?p=ulastirma-ve-haberlesme-112&dil=1, (16.08.2023)
• UN, 2023. United Nations (UN)- World Sustainable Day. https://www.un.org/en/observances/sustainable-transport-day, (06.12.2023)
• UN-Habitat, 2022. World Cities Report 2022. United Nations Human Settlements Programme (UN-Habitat). https://unhabitat.org/sites/default/files/2022/06/wcr_2022.pdf, (05.12.2023)
• UN-Interagency Report, 2021. Sustainable Transport, Sustainable Development. Interagency Report For Second Global Sustainable Transport Conference. https://sdgs.un.org/sites/default/files/2021-10/Transportation%20Report%202021_FullReport_Digital.pdf, (06.12.2023)