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1
International Symposium on Applied Geoinformatics (ISAG2021)
TEMPORAL COMPARISON OF BETWEENNESS IN SUBURBAN REGIONS OF
ISTANBUL, TURKEY
Ömer Akın1, Hande Demirel 1
1Istanbul Technical University, Faculty of Civil Engineering, Department of Geomatics Engineering, Istanbul, Turkey
(akinom/hande.demirel@itu.edu.tr); ORCID 0000-0002-8109-0313, ORCID 0000-0003-0338-791X
1. Introduction
The transport infrastructure in populated cities becomes more complex over time and the contribution of new investments
is difficult to discern. If the relationship between investments and their performance is not fully assessed, the region may
have to cope with uncontrolled urbanization and increased network complexity. To assess this relationship quantitatively,
the topological and geometric distribution of network elements should be evaluated in terms of their importance in the
network.
There are quantitative analyzes and indicators in the literature that are tailored to transportation networks and serve as
benchmarks to identify network changes in performance (Boeing, 2017). These indicators characterize network elements
(nodes and links) considering their different topological properties. Among these indicators, betweenness is an indicator
developed to find out how many of the shortest paths in the network pass through the edge or node in question, and in this
sense, it is used to determine the critical elements in a transportation network (Crucitti et al., 2006; Sevtsuk and Mekonnen,
2012). The metric is used in several studies to monitor volume of traffic (Puzis et al., 2013), to measure the network's
vulnerability to disasters (Iqbal and Kuipers, 2017), and to determine the urban changes in relation to traffic (Barthelemy
et al., 2013).
In this study, betweenness analyses was conducted for a developing region in Istanbul, Turkey for the years 2007, 2014
and 2021 to assess the performance of road investments quantitatively and spatially. The critical intersections in terms of
shortest paths were determined, compared and the changes in spatial distribution were evaluated.
2. Materials and Methods
The selected study area is a suburban region on the European side of Istanbul. It is located between the Lake Küçükçekmece
and Büyükçekmece and consists of three districts, namely Beylikdüzü, Esenyurt and Avcılar. Especially after 2007, when
the Bus Rapid Transit (BRT) route Metrobus started to operate, urbanization increased in the region, which led to the
development of new roads in these regions.
The road network data for the region was acquired from the OpenStreetMap (OSM) database for the year 2021 and the
node-link topology was structured. Then, satellite images were used to obtain the road network for the years 2007 and 2014.
In the study, the node-based betweenness centrality metric was used to identify the important intersections in the network
for the selected years. The metric is based on graph theory, where the network is represented as a set of elements and the
connections between them, namely nodes and links (Trudeau, 2013, Porta et al., 2006). The betweenness centrality of a
node can be described as the sum of the proportion of all pairs of shortest paths passing through the node and formulated
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International Symposium on Applied Geoinformatics (ISAG2021)
2-3 December 2021, Riga, Latvia
as in Eq. (1);
(1)
where is the set of nodes, is the number of shortest paths, and is the number of the shortest paths passing
through the node .
All steps of data processing and analysis were performed using the open-source Python programming language and its
libraries, namely geopandas, momepy, numpy, scipy and networkx. QGIS software was used for mapping.
3. Results and Discussion
By using the road network data of each year, the betweeenness of each node was calculated, and the number of nodes, mean
and median betweenness values are presented in Table 1.
Table 1. Betweenness statistics
2007
2014
2021
Number of Nodes
11562
15443
18365
Mean
4.7
3.8
3.4
Median
0.7
0.5
0.4
As it can be seen in Table 1, the mean and median betweenness values decreased even though the number of nodes increased.
That means that the shortest distances between nodes decreased. This trend could be interpreted as the distribution of nodes
carrying the main traffic is better optimized.
The results should be enriched by considering the spatial distribution of these important nodes. The selected region
represents a complex transportation network that has a high number of interconnection points as can be seen in Table 1. To
interpret such data, the distribution of the data should be taken with caution. The data was evaluated with the histograms
shown in Figure 1.
Figure 1 Distribution of betweenness values
As it can be seen from the graphs, the data are skewed to the right. The reason for this is that the study area is urbanized
and has many local roads that connect the hinterland to the main roads. The nodes connecting local roads are the least used
ones, considering the shortest paths between the whole network nodes; and as a result, their betweenness values are very
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International Symposium on Applied Geoinformatics (ISAG2021)
2-3 December 2021, Riga, Latvia
close to zero. This type of distribution bring complexity to represent the correct information. For this reason, using to the
distribution and statistics shown in Figure 1, nodes above the 90th percentile were selected for the presentation of main
arterials for selected years. The betweenness patterns for the selected nodes are shown in Figure 2.
Figure 2 Betweenness patterns for the year a) 2007, b) 2014, c) 2021
Examination of the betweenness patterns reveals that, between 2007 and 2014, the northern part (Esenyurt district) and
between 2014 and 2021, both northern part and southern part (Beylikdüzü) have experienced significant urbanization,
resulting in the increase in the road network. The number of nodes with higher betweenness values has increased
significantly in these regions. In addition, there seems to be a trend over the years that nodes with very high values on
arterials are more homogeneously distributed on collector roads. These results can be taken as an indication that these new
roads are well suited for the shortest routes spatially.
4. Conclusion
The aim of this study was to determine the performance of the road network as a result of newly constructed roads in a
developing part of Istanbul. By examining both quantitative and spatial results, it was found that the new roads contribute
in a positive way to a homogeneous distribution. Such studies can be used to evaluate network performance by
quantitatively presenting the effect of road investments in terms of their impact on the distribution of density in the network.
Keywords: Network Analysis, Urban Transportation, Performance Indicators, Betweenness Centrality
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International Symposium on Applied Geoinformatics (ISAG2021)
2-3 December 2021, Riga, Latvia
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