Eskişehir Kent Merkezindeki Trafik Kazalarının Zamana Bağlı Konumsal Analizi

Year 2023, , 17 - 32, 28.03.2023

Vural Yıldırım , Erdem Yurdakul , Gökben Adana Karaağaç , Merve Koçer , Hakan Uyguçgil

https://doi.org/10.48123/rsgis.1167844

Cited By: 2

Abstract

Trafik kazalarının önlenmesinde ilk yapılması gereken işlem kazaların yoğunlaştığı noktaların belirlenmesidir. Bu amaçla 2010-2019 yılları arasında Eskişehir kent merkezinde meydana gelen trafik kazaları istatistiksel olarak benzer, yaklaşım olarak farklı iki yöntem kullanılarak analiz edilmiştir. Çalışmada önce klasik sıcak nokta analizi kullanılmış ve 15 sıcak nokta tespit edilmiştir. Daha sonra aynı veri seti konum-zaman küpü kullanılarak zamana bağlı sıcak nokta yöntemi ile analiz edilmiş, 50 aralıklı, 10 yeni, 7 ardışık, 4 sürekli, 1 azalan ve 1 yoğunlaşan olmak üzere toplam 73 sıcak nokta bulunmuştur. İki yöntemin sonuçları kıyaslandığında, zamana bağlı sıcak nokta analizi ile 1. bölgedeki sıcak nokta sayısının 6'dan 19'a, 2. bölgedeki sıcak nokta sayısının 2'den 20'ye, 3. bölgedeki sıcak nokta sayısının 3'den 12'ye, 4. bölgedeki sıcak nokta sayısının 3'den 11'e ve 5. bölgedeki sıcak nokta sayısının 1'den 11'e çıktığı görülmüştür. Klasik sıcak nokta analizine kıyasla zamana bağlı sıcak nokta analizi ile farklı konumlarda ve farklı desenlerde daha çok trafik kazası sıcak noktalarının tespit edilmesi, konumun ve zamanın bir arada kullanılmasının önemini ortaya koymaktadır. Çalışma sonucunda zamana bağlı sıcak nokta analizinin klasik sıcak nokta analizine göre daha detaylı sonuçlar verdiği gözlemlenmiştir.

Keywords

Coğrafi Bilgi Sistemleri, Trafik kazaları, Konum-zaman küpü yöntemi, Klasik sıcak nokta analizi, Zamana bağlı sıcak nokta analizi

Spatiotemporal Analysis of Traffic Accidents in Eskişehir City Center

Abstract

The first thing to do in preventing traffic accidents is to determine the spots where the accidents are concentrated. For this purpose, traffic accidents in Eskişehir city center that occurred between 2010-2019 were analyzed using two methodologies those are statistically similar but different in approaches. Firstly, classical hot spot analysis was performed, and 15 hot spots were found. Subsequently, the same data set was analyzed with the emerging hot spot using the space-time cube method, and a total of 73 hot spots were detected, including 50 sporadic, 10 new, 7 consecutive, 4 persistent, 1 diminishing, and 1 intensifying. A comparison of the results of the two methodologies shows an increase in the number of hot spots in the first region from 6 to 19, in the second region from 2 to 20, in the third region from 3 to 12, in the fourth region from 3 to 11 and in the fifth region from 1 to 11. Finding more hot spots in different locations and patterns with emerging hot spot analysis proportional to classical hot spot analysis reveals the importance of using location and time together. As a result of the study, it was observed that the emerging hot spot analysis provides more detailed outcomes whence the classical hot spot analysis.

Keywords

Geographic Information Systems, Traffic accidents, Space-time cube method, Classical hot spot analysis, Emerging hot spot analysis

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