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The Application of Geographic Information System (GIS) on Five Basic Indicators of Sustainable Urban Transport Performance

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Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 224)

Abstract

As the era of information technology today, the use of digital information is very useful in the process of data collection, analysis and modeling. A Geographical Information Systems (GIS) is not only a tool, but it is also has a powerful ability in the analysis process, included to measure the performance of transportation in sustainability issues. The purpose of this study is to show how GIS can be used to analyze Sustainable Urban Transport performance based on its basic indicators. This paper used literature review in the field of GIS approach in sustainable urban transport studies with using classification methods from the sources with certain procedure. The paper shows the GIS application in urban transport performance studies on five basic indicators: traffic congestion, traffic air pollution, traffic noise pollution, traffic accident and transport infrastructure. The study found that the use of GIS in urban transport performance studies is dominant on traffic congestion indicator and the tool of GIS which used to measure transport performance mainly by the shortest path. It is interesting how to measure the performance of Sustainable Urban Transport (SUT) to be more comprehensive with involves all basic indicators i.e. traffic congestion, traffic air pollution, traffic noise pollution, traffic accident and transport infrastructure.

Keywords

  • GIS
  • Sustainable urban transport
  • Basic indicator
  • Performance

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Correspondence to Puji Adiatna Nadi .

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Nadi, P.A., Murad, A. (2018). The Application of Geographic Information System (GIS) on Five Basic Indicators of Sustainable Urban Transport Performance. In: Mehmood, R., Bhaduri, B., Katib, I., Chlamtac, I. (eds) Smart Societies, Infrastructure, Technologies and Applications. SCITA 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 224. Springer, Cham. https://doi.org/10.1007/978-3-319-94180-6_26

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  • DOI: https://doi.org/10.1007/978-3-319-94180-6_26

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