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@proceedings{1594462,
author = {Shen, Jie and Zang, Kaiyue and Li, Hanchen and Du, Yixian and Zhong, Linying and Šilhák, Petr},
booktitle = {International Symposium on Location-Based Big Data 2019},
keywords = {Dynamic visualization; Road waterlogging; Early Warning; User location; Travel Route},
language = {eng},
title = {Dynamic visualization method for the road waterlogging early warning based on the user location},
year = {2019}
}
TY - CONF
ID - 1594462
AU - Shen, Jie - Zang, Kaiyue - Li, Hanchen - Du, Yixian - Zhong, Linying - Šilhák, Petr
PY - 2019
TI - Dynamic visualization method for the road waterlogging early warning based on the user location
KW - Dynamic visualization
KW - Road waterlogging
KW - Early Warning
KW - User location
KW - Travel Route
N2 - With the increasing amount of user location-based big data, massive trajectory data, social media data (e.g., Twitter, Flickr), crowdsourced geographic information and the improvement of processing and mining technology, real-time visualization of urban daily traffic information has become possible. The urban transportation system, as the basic skeleton of the city, is not only the carrier of daily travel passengers and cargo transportation, but also a kind of disastertolerant body with extremely high vulnerability in the waterlogging disaster (Yin, Yu, and Wilby 2016). A large number of historical experiences have shown that meteorological disasters often cause urban traffic jams and even paralysis of the urban transportation system. As one of the meteorological disasters, urban waterlogging often occurs in the Yangtze river delta region in summer, which seriously impedes the normal operation of the urban traffic system. How to add real-time weather information into the existing travel route planning has become a hot issue of location-based navigation.
ER -
SHEN, Jie, Kaiyue ZANG, Hanchen LI, Yixian DU, Linying ZHONG a Petr ŠILHÁK. Dynamic visualization method for the road waterlogging early warning based on the user location. In \textit{International Symposium on Location-Based Big Data 2019}. 2019.
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