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Fundamental Research for the Creation of a Global Human Flow Data Commons

Research Project

Project/Area Number 22K18498
Research Category

Grant-in-Aid for Challenging Research (Exploratory)

Allocation TypeMulti-year Fund
Review Section Medium-sized Section 4:Geography, cultural anthropology, folklore, and related fields
Research InstitutionThe University of Tokyo

Principal Investigator

SEKIMOTO YOSHIHIDE  東京大学, 空間情報科学研究センター, 教授 (60356087)

Co-Investigator(Kenkyū-buntansha) 樫山 武浩  大阪経済大学, 経済学部, 准教授 (10611155)
矢部 貴大  東京大学, 空間情報科学研究センター, 客員研究員 (30940431)
Pang Yanbo  東京大学, 空間情報科学研究センター, 特任助教 (60870178)
小川 芳樹  東京大学, 空間情報科学研究センター, 講師 (70794296)
瀬戸 寿一  駒澤大学, 文学部, 准教授 (80454502)
澁谷 遊野  東京大学, 空間情報科学研究センター, 准教授 (20847917)
Project Period (FY) 2022-06-30 – 2024-03-31
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000)
Fiscal Year 2023: ¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
Fiscal Year 2022: ¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
Keywords擬似人流 / デジタルツイン / 自動抽出 / 建物 / 人流 / グローバル / データコモンズ
Outline of Research at the Start

近年の都市政策は、人口減少、高齢化、予算緊縮、コンパクトシティの推進等など様々な要因が加わり、複雑化している。
一方でそうした分析の中心となる人々の活動・流動を取り上げてみても、例えば民間ベースの携帯端末データをもとにした時間帯別メッシュ人口データは、集計ベースであっても依然高価であり、また、データの入手状況やその品質に応じて結果が大きく変わる不安定な状態が長く続いている。
そこで、本研究では、様々な国や地域の政策現場で汎用的に活用できることを念頭に置いた「全球規模の各国レベルの擬似人流データ基盤とそのエージェントモデル」を構築する事を目標にした基礎的な研究を進めていく。

Outline of Final Research Achievements

In this study, we were going to conduct basic research with the goal of constructing a “global-scale, country-level pseudo-human flow data infrastructure and its agent models” that can be used universally in various countries and regions for policy making. The results of the research include the world's first creation of nationwide pseudo-human flow data (three types of agents and seven types of actions) for 130 million people covering all of Japan, the use of millions of real POI data for destination selection candidates from the jointly used data (JoRAS) of the Center for Spatial Information Science, to which the company belongs, and the use of parameters for transportation mode selection based on historical statistics for each area. We were also able to release Ver. 2.0, which has more realism by changing the parameters based on past statistics for each area.

Academic Significance and Societal Importance of the Research Achievements

これまで携帯端末による人流データは商業的にも広まってきているものの、プライバシーの関係上、集計データに限られる事が多かったり、それでも値段も大変高価であった。そのような意味で、全国をカバーし、シミュレーションが行いやすいデータ基盤として、都市計画・交通計画等、公益に資する活動のための基礎データの整備が行われたのは大変意義が大きい。

Report

(3 results)
  • 2023 Annual Research Report   Final Research Report ( PDF )
  • 2022 Research-status Report
  • Research Products

    (7 results)

All 2024 2023 2022 Other

All Journal Article (2 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 2 results,  Open Access: 2 results) Presentation (4 results) (of which Int'l Joint Research: 3 results) Remarks (1 results)

  • [Journal Article] Nationwide Synthetic Human Mobility Dataset Construction from Limited Travel Surveys and Open Data2024

    • Author(s)
      Takehiro Kashiyama, Yanbo Pang, Yuya Shibuya, Takahiro Yabe, Yoshihide Sekimoto
    • Journal Title

      Computer-Aided Civil and Infrastructure Engineering

      Volume: -

    • Related Report
      2023 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Large-scale individual building extraction from open-source satellite imagery via super-resolution-based instance segmentation approach2023

    • Author(s)
      Chen, S., Ogawa, Y., Zhao, C., & Sekimoto, Y.
    • Journal Title

      ISPRS Journal of Photogrammetry and Remote Sensing

      Volume: 195 Pages: 129-152

    • DOI

      10.1016/j.isprsjprs.2022.11.006

    • Related Report
      2022 Research-status Report
    • Peer Reviewed / Open Access
  • [Presentation] Deep Learning Approach to Logistics Trips Generation: Enhancing Pseudo People Flow with Agent-based Modeling2023

    • Author(s)
      Zhang, K., Pang, Y., and Sekimoto, Y
    • Organizer
      IEEE ITS Annual Conference
    • Related Report
      2023 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Synthetic Network Traffic Data Generation using Deep Generative Models2023

    • Author(s)
      Yanbo Pang, Pierre Ferry, Kunyi Zhang
    • Organizer
      Netmob 2023
    • Related Report
      2023 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Large-scale building footprint extraction from open-sourced satellite imagery via instance segmentation approach2022

    • Author(s)
      Chen, S., Ogawa, Y., Zhao, C., and Sekimoto, Y.
    • Organizer
      IGRASS2022
    • Related Report
      2022 Research-status Report
    • Int'l Joint Research
  • [Presentation] 全国擬似人流データの提供と評価2022

    • Author(s)
      ホウ岩博,樫山武浩,関本 義秀
    • Organizer
      第31回地理情報システム学会
    • Related Report
      2022 Research-status Report
  • [Remarks] 「擬似人流とは」(人の流れプロジェクト内)

    • URL

      https://pflow.csis.u-tokyo.ac.jp/data-service/pseudo-pflow/

    • Related Report
      2023 Annual Research Report 2022 Research-status Report

URL: 

Published: 2022-07-05   Modified: 2025-01-30  

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