Publication

@conference{kasahara2022_GIS-理論と応用b,

title = {ベクトルタイル技術を用いた全国規模の人流データの効率的な可視化},

author = {笠原有貴 and 関本義秀 and 樫山武浩 and 瀬崎薫},

url = {https://www.gisa-japan.org/publications/about.html},

year  = {2022},

date = {2022-12-01},

urldate = {2022-12-01},

journal = {GIS-理論と応用},

volume = {30},

number = {2},

pages = {85-90},

abstract = {In recent years, it has become important to understand people flow in various fields. However, most of the methods to understand people flow are limited to urban areas, and there are few studies that have been conducted on a nationwide scale using pseudo people flow data. In addition, by using vector tiling technology in data visualization and changing the granularity of the data according to the zoom level, the amount of data can be saved and the processing speed can be improved. Therefore, in this study, we created pseudo people flow data covering about 120 million people on a nationwide scale using the vector tiling technology, and visualized the data to understand the actual situation. As a result, the amount of data has been reduced to about 57%, and efficient visualization can be performed with the necessary information displayed according to the zoom level, including rural areas.},

keywords = {ベクトルタイル, 人流データ, 全国規模, 可視化},

pubstate = {published},

tppubtype = {conference}

}

@conference{gis_kasahara2022,

title = {擬似人流データにおける時刻表を考慮した自治体全域の交通手段の推計 ー静岡県裾野市を対象にー},

author = {笠原有貴 and 龐岩博 and 樫山武浩 and 関本義秀 and 瀬崎薫},

url = {https://www.gisa-japan.org/conferences/},

year  = {2022},

date = {2022-10-29},

urldate = {2022-10-29},

booktitle = {地理情報システム学会 第31回学術研究発表大会（沖縄）},

abstract = {In recent years, it has become important to understand people flow in various fields such as infectious disease control, and there are various types of means of understanding people flow, such as GPS data and person-trip survey data. However, these data are difficult to share due to privacy protection issues. Based on this, Kashiyama et al. have developed simulations using statistical data to create pseudo-people flow data, which can be shared. Although this data is highly accurate, it does not take into account timetables in terms of people's traffic behavior, which would improve the accuracy by reproducing traffic behavior according to timetables. In this study, we evaluated the accuracy of the pseudo-people flow data created by Kashiyama et al. for Susono City, Shizuoka Prefecture, by estimating the transportation modes with timetables taken into account.},

keywords = {GTFS, 交通手段選択, 人流データ},

pubstate = {published},

tppubtype = {conference}

}