TEMPORAL AND SPATIAL ANALYSIS OF TRAFFIC ACCIDENTS: THE CASE OF BURSA CITY

The increase in the population over time in Turkey causes an increase in the number of vehicles. In turn, the increase in the number of vehicles hampers urban transportation. Congested traffic results in a number of problems. One of these problems is traffic accidents. In this study, traffic accidents which occurred in five central districts of Bursa were investigated in terms of temporal, spatial and temporal-spatial. The reason for choosing the central districts is that traffic accidents occur more intensively in these districts than other districts. The data used in this study include traffic accident data from 2015 to 2020 and land use data for 2018. ArcGIS 10.8 and ArcGIS Pro 2.5 version were used to identify analyses and findings. In ArcGIS version 10.8 point density, collect events, Anselin Local Moran I, Emerging Hot Spot Analysis and 2D Visualize Space Time Cube tools were used. Time, day, month, season and year information were included in the time related analyzes of traffic accidents. Land use, district, neighborhood and highway data were used in spatial analysis. As a result of this study, findings were determined under three subtitles. These were temporal, spatial and temporal-spatial titles. When examined in terms of time, only the year 2020 drew attention out of five years. This resulted from pandemics. Seasonally, the lowest number of traffic accidents were recorded in winter while the highest were recorded in summer. When the distribution of traffic accidents according to highways was examined under the title of spatial, the most occurred on Ankara Street. Finally, it was determined that traffic accidents, which were examined under the title of temporal-spatial, were intense in residential areas and industrial areas.

TEMPORAL AND SPATIAL ANALYSIS OF TRAFFIC ACCIDENTS: THE CASE OF BURSA CITY

The increase in the population over time in Turkey causes an increase in the number of vehicles. In turn, the increase in the number of vehicles hampers urban transportation. Congested traffic results in a number of problems. One of these problems is traffic accidents. In this study, traffic accidents which occurred in five central districts of Bursa were investigated in terms of temporal, spatial and temporal-spatial. The reason for choosing the central districts is that traffic accidents occur more intensively in these districts than other districts. The data used in this study include traffic accident data from 2015 to 2020 and land use data for 2018. ArcGIS 10.8 and ArcGIS Pro 2.5 version were used to identify analyses and findings. In ArcGIS version 10.8 point density, collect events, Anselin Local Moran I, Emerging Hot Spot Analysis and 2D Visualize Space Time Cube tools were used. Time, day, month, season and year information were included in the time related analyzes of traffic accidents. Land use, district, neighborhood and highway data were used in spatial analysis. As a result of this study, findings were determined under three subtitles. These were temporal, spatial and temporal-spatial titles. When examined in terms of time, only the year 2020 drew attention out of five years. This resulted from pandemics. Seasonally, the lowest number of traffic accidents were recorded in winter while the highest were recorded in summer. When the distribution of traffic accidents according to highways was examined under the title of spatial, the most occurred on Ankara Street. Finally, it was determined that traffic accidents, which were examined under the title of temporal-spatial, were intense in residential areas and industrial areas.

___

  • Ağaoğlu, M. N., & Başdemir, H. (2019). Kent içi ulaşim sorunları ve çözüm önerileri. Gaziosmanpaşa Bilimsel Araştırma Dergisi, 8(1), 27-36.
  • Aghajani, M. A., Dezfoulian, R. S., Arjroody, A. R., & Rezaei, M. (2017). Applying GIS to Identify the spatial and temporal patterns of road accidents using spatial statistics (case study: Ilam Province, Iran). Transportation Research Procedia, 25, 2126-2138.
  • Ağın, C. (2015). Türkiye’de şehirlerdeki toplu ulaşım sistemleri sorunlarının çözümlenmesinde toplumsal davranışların etkilerinin planlama süreci kapsamında incelenmesi. İzmir-Karşıyaka örneği. (Yüksek lisans tezi, Dokuz Eylül Üniversitesi, Fen Bilimleri Enstitüsü, İzmir). https://tez.yok.gov.tr/UlusalTezMerkezi/ adresinden edinilmiştir.
  • Ali Haidery, S., Ullah, H., Ullah Klan, N., Fatima, K., Rizvi, S. S., & Kwon, S. J. (2020). Role of Big Data in the development of smart city by analyzing the density of residents in Shanghai. Electronics, 9(5), 1-16.
  • Ali, R., Khan, M. R., & Mehmood, H. (2017). Incidence of violence risk mapping using GIS: A case study of Pakistan. Journal of Geographic Information System, 9(6), 623-636.
  • Aronoff, S. (1989). Geographic Information Systems: A management perspective. Geocarto International, 4(4), 58-58.
  • BBB (Bursa Büyükşehir Belediyesi) (2021). 19 Mayıs 2021 tarihinde https://www.bursa.com.tr/tr/sayfa/nufus-konum-iklim-ve-cografya- 47/, adresinden edinilmiştir.
  • Çağlıyan, A., Dağlı, D., & Ayhan, G. (2016). Traffic accident analysis of the city of Elazığ by Geographical Information System. 4th International Geography Symposium. Antalya, Turkey.
  • Çiçek, M. (2007). Trafik bilgi sistemi verileri ile Ankara ili trafik güvenliğinin incelenmesi. (Yüksek lisans tezi, Gazi Üniversitesi, Fen Bilimleri Enstitüsü, Ankara). https://tez.yok.gov.tr/UlusalTezMerkezi/ adresinden edinilmiştir.
  • Cınar, H. S., & Cermikli, B. (2019). Point density analysis with cognitive mapping technique: Istanbul-Historical City Center. Fresenius Environmental Bulletin, 28(12), 9192-9199.
  • Climate-Data (Climate-Data.Org) (2021). 19 Mayıs 2021 tarihinde https://tr.climate-data.org/asya/tuerkiye/bursa/bursa-714886/, adresinden edinilmiştir.
  • Copernicus (2021). 10 Mayıs 2021 tarihinde https://land.copernicus.eu/local/urban-atlas/urban-atlas-2018, adresinden edinilmiştir.
  • Corso, A. J., Leroy, G., & Alsusdais, A. (2015). Toward predictive crime analysis via Social Media, Big Data, and GIS, and GIS spatial correlation. In iConference 2015’te sunulmuştur. Newport Beach. CA, USA.
  • Costache, R., & Popescu, C. (2013). The touristic accessibility in the Hunedoara county in terms of road network. Geographia Technica, 8(12), 1-12.
  • Dereli, M. A. (2016). Trafik kaza kara noktalarının belirlenmesi için Coğrafi Bilgi Sistemleri (CBS) destekli mekânsal istatistiksel metotlar ile bir model geliştirilmesi. (Doktora tezi, Afyon Kocatepe Üniversitesi, Fen Bilimleri Enstitüsü, Afyon). https://tez.yok.gov.tr/UlusalTezMerkezi/ adresinden edinilmiştir.
  • Dezman, Z., De Andrade, L., Vissoci, J. R., El-Gabri, D., Johnson, A., Hirshon, J. M., & Staton, C. A. (2016). Hotspots and causes of motor vehicle crashes in Baltimore, Maryland: A geospatial analysis of five years of police crash and census data. Injury, 47(11), 2450-2458.
  • Geofabrik (2021). 14 Şubat 2021 tarihinde https://download.geofabrik.de/europe/turkey.html, adresinden edinilmiştir.
  • Getis, A., & Ord, J. (1995). Local spatial autocorrelation statistics: Distributional issues and an application. State University Press, 27.
  • Geymen, A. & Dedeoğlu, O. K. (2016). Coğrafi Bilgi Sistemlerinden yararlanılarak trafik kazalarının azaltılması: Kahramanmaraş ili örneği. Iğdır Üni. Fen Bilimleri Enst. Der., 6(2), 79-88.
  • Goodchild, M. F. (2018). Reimagining the history of GIS. Annals of GIS, 24(1), 1-8.
  • Haybat, H., & Karakaş, E. (2018). An analysis of traffic accidents with spatial statistical methods in Izmir Province. Social Science Development Journal, 3, 599-617.
  • Haybat, H., & Karakaş, E. (2020). Relationship between daily activity areas and traffic accidents in İzmir city. International Journal of Geography and Geography Education (IGGE), 42, 429-454.
  • Kababulut, F. Y., & Helvacı, C. (2017). Büyük şehirlerde ulaşım sistemleri ve sorunları: İzmir ili özelindeki sorunlara çözüm önerileri. Planlama, 27(3), 215-221.
  • Karakaş, E., Aslan, H., & Karadoğan, S. (2009). Elazığ şehrindeki trafik kazalarıyla iklim ilişkisinin analizi. Nature Sciences, e-Journal of New World Sciences Academy, 4(3), 53-69.
  • Karaman, E. (2013). İstanbul'da meydana gelen trafik kazalarının mekansal analizi. (Yüksek lisans tezi, Fatih Üniversitesi, Sosyal Bilimler Enstitüsü, İstanbul). https://tez.yok.gov.tr/UlusalTezMerkezi/ adresinden edinilmiştir.
  • Kendall, M. G., & Gibbons, J. D. (1990). Rank correlation methods. London: Oxford University Press.
  • Kundakçı, E. (2014). Identification of traffic accident hot spots and their characteristics in urban area by using GIS. (Master’s thesis, Middle East Technical University, Geodetic and Geographic Information Technologies, Ankara). Retrieved from https://tez.yok.gov.tr/UlusalTezMerkezi/.
  • Kuo, P., Lord, D., & Walden, T. D. (2013). Using Geographical Information Systems to organize police patrol routes effectively by grouping hotspots of crash and crime data. Journal of Transport Geography, 30, 138-148.
  • Kuşkapan, E., Alemdar, K. D., Kaya, Ö., & Çodur, M. Y. (2019). Traffic accidents caused by pedestrians in Turkey. International Journal for Traffic and Transport Engineering, 9(1), 118-126.
  • Levine, J. & Landis, J. D. (1989). Geographic Information Systems for local planning. Journal of the American Planning Association, 55(2), 209-220.
  • Levine, N., Kim, K., & Nitz, L. (1995). Spatial analysis of Honolulu motor vehicle crashes: Part I: Spatial patterns. Accident Analysis and Prevention, 27(5), 663-674.
  • Li, Y., Abdel-Aty, M., Yuan, J., Cheng, Z., & Lu, J. (2020). Analyzing traffic violation behavior at urban intersections: A spatiotemporal Kernel Density estimation approach using automated enforcement system data. Accident Analysis and Prevention, 141, 105-509.
  • Mann, H. B. (1945). Nonparametric tests against trend. Econometrica, 13, 245-59.
  • Marti-Henneberg, J. (2011). Geographical Information Systems and the study of history. Journal of Interdisciplinary History, 42(1), 1-13.
  • Mohammed, A. A., Ambak, K., Mosa, A. M., & Syamsunur, D. (2019). A review of the traffic accidents and related practices worldwide. The Open Transportation Journal, 13, 65-83.
  • Nitin, G., & Adnan, A. H. (2006). Exploring the relationship between development and road traffic injuries: A case study from India. European Journal of Public Health, 16(5), 487-491.
  • Okafor, K., Azuike, E., & Okojie, P. (2017). The causes and prevalence of road traffic accidents amongst commercial long distance drivers in Benin City, Edo State, Nigeria. Nigerian Journal of Medicine, 26(3), 220- 230.
  • Özlü, T., Haybat, H., & Zerenoğlu, H. (2020). Temporal and spatial analysis of traffic accidents: The case of Eskişehir City. International Journal of Geography Education (IGGE), 43, 136-158.
  • Peuquet, D. J., & Marble, D. F. (1990). Introductory readings in Geographic Information Systems. USA: Taylor & Francis.
  • Said, S. N. B. M., Zahran, E. M. M., & Shams, S. (2017). Forest fire risk assessment using hotspot analysis in GIS. The Open Civil Engineering Journal, 11(1), 786-801.
  • Soltani, A., & Askari, S. (2014). Analysis of Intra-urban traffic accidents using spatiotemporal visualization techniques. Transport and Telecommunication, 15(3), 227-232.
  • Suphanchaimat, R., Sornsrivichai, V., Limwattananon, S., & Thammawijaya, P. (2019). Economic development and road traffic injuries and fatalities in Thailand: An application of Spatial Panel Data Analysis, 2012–2016. BMC Public Health, 19(1), 1-15.
  • TÜİK (Türkiye İstatistik Kurumu), (2021). 23 Haziran 2021 tarihinde http://www.tuik.gov.tr, adresinden edinilmiştir.
  • Tümertekin, E. (1987). Ulaşım coğrafyasi. İstanbul: İstanbul Üniversitesi Yayınları.
  • Tuncuk, M. (2004). Coğrafi Bilgi Sistemi yardımıyla trafik analizi: Isparta örneği. (Yüksek lisans tezi, Süleyman Demirel Üniversitesi, Fen Bilimleri Enstitüsü, Isparta). https://tez.yok.gov.tr/UlusalTezMerkezi/ adresinden edinilmiştir.
  • UNECE (The United Nations Economic Commission for Europe), (2020). 20 Mart 2020 tarihinde https://www.unece.org/unrsf/about-the- fund.html, adresinden edinilmiştir.
  • Waters, N. (2017). The international encyclopedia of geography. New York: John Wiley & Sons.
  • WHO (World Health Organization), (2018). 06 Mayıs 2020 tarihinde https://www.who.int/gho/publications/world_health_statistics/2018/e n/, adresinden edinilmiştir.
  • Yardımcıoğlu, F. (2013). Ulaşım hizmetleri (kamu hizmetleri perspektifi). Bursa: Dora Yayıncılık.
  • Zerenoğlu, H. (2020). Trafik kazalarının mekânsal analizi: Eskişehir örneği, (Yüksek lisans tezi, Ondokuz Mayıs Üniversitesi, Lisansüstü Eğitim Enstitüsü, Samsun). https://tez.yok.gov.tr/UlusalTezMerkezi/ adresinden edinilmiştir.
  • Zou, X., & Vu, H. L. (2019). Mapping the knowledge domain of road safety studies: A scientometric analysis. Accident Analysis and Prevention, 132, 105-243.