2015
DOI: 10.1007/s12205-015-0694-4
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Proposal for the generation of network data for pedestrians in South Korea using large-scale maps

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Cited by 3 publications
(5 citation statements)
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“…This dataset was constructed based on the digital map produced by National Geographic Information Institute (NGII) of Korea. In addition, it was constructed according to the methodology of Kim et al (2015) [ 14 ], using the existing road dataset and partly manual post-processing.…”
Section: Experimental Results and Assessmentmentioning
confidence: 99%
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“…This dataset was constructed based on the digital map produced by National Geographic Information Institute (NGII) of Korea. In addition, it was constructed according to the methodology of Kim et al (2015) [ 14 ], using the existing road dataset and partly manual post-processing.…”
Section: Experimental Results and Assessmentmentioning
confidence: 99%
“…On the other hand, methodologies that have used pre-existing road data were also developed. Kim et al [ 13 , 14 ] generated a pedestrian road network for PNS by utilizing existing spatial datasets. Liu et al [ 15 ] proposed the rules and logic model and attributes for a pedestrian network and proposed a connecting model with an existing vehicle network.…”
Section: Introductionmentioning
confidence: 99%
“…The census data were originally created by a phone carrier in South Korea, and they could be extracted from the Seoul City GIS data warehouse. The network data developed by Kim et al (2015) were also acquired from the government website. The network barriers were extracted from the network dataset using its attribute.…”
Section: Data Description and Processmentioning
confidence: 99%
“…In normal situations, a certain time lag is added to these network impedances. However, under emergency situations, these network impedances can be Meanwhile, the pedestrian network dataset developed by Kim et al (2015) was utilized for a more precise analysis. The precision, which was compared with a real-world pedestrian network, calculated from the F-measure was 0.991, which reflects almost all real-world walkways [29].…”
Section: Data Description and Processmentioning
confidence: 99%
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