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Shohei Nagata

Section

International Research Institute of Disaster Science

Job title

Assistant Professor

Degree

Ph.D. (Tohoku University)

researchmap

https://researchmap.jp/shohei_nagata

J-GLOBAL ID

202201012404939091

e-Rad No.

10966063

ORCID

https://orcid.org/0000-0001-7043-9981

Research History 5

2025/11 - Present

University of Washington　Civil & Environmental Engineering　Visiting Scholar
2023/04 - Present

Tohoku University　International Research Institute of Disaster Science　Assistant Professor
2022/04 - 2023/03

Tohoku University　Graduate School of Environmental Studies
2018/10 - 2019/03

Tohoku University　Graduate School of Environmental Studies
2015/04 - 2018/08

ESRIジャパン株式会社

Education 3

Tohoku University　Graduate School of Environmental Studies　Department of Frontier Sciences for Advanced Environment

2019/04 - 2022/03
Ritsumeikan University　Graduate School of Letters

2013/04 - 2015/03
Ritsumeikan University　College of Letters　Department of Humanities Geography Major

2008/04 - 2012/03

Committee Memberships 1

東北地理学会　季刊地理学編集委員会

2025/06 - Present

Professional Memberships 6

American Association of Geographers
日本地理学会
地理情報システム学会
日本疫学会
東北地理学会
立命館地理学会

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Research Interests 7

Disaster Science
Human Mobility
Spatial Epidemiology
Urban Informatics
Geographic Information Science
Health Geography
Walkability

Research Areas 5

Social infrastructure (civil Engineering, architecture, disaster prevention) / Disaster prevention engineering /
Informatics / Statistical science /
Life sciences / Healthcare management, medical sociology / Public Health
Humanities & social sciences / Human geography /
Humanities & social sciences / Geography /

Awards 6

環境科学研究科長賞

2022/03　東北大学大学院環境科学研究科
3rd Place-3D Map, 2021 Esri User Conference

2021/07　Esri　Gaihozu Viewer: Indonesian-territory version - Historical maps made by former Japanese Imperial Army
1st Place-Analytic Method and Results and 1st Place-Most Innovative Map, 2021 Esri User Conference

2021/07
第17回GISコミュニティフォーラムマップギャラリー2021 マップ部門第1位

2021/05　ESRIジャパン株式会社　COVID-19流行はDOKODE続いているか：COVID-19時空間３Dマップ
理学・生命科学2研究科合同オンラインシンポジウム2021 優秀ポスター賞

2021/02　東北大学大学院理学研究科　COVID-19流行とモビリティ変化の関連：モバイルデバイスデータに基づく分析
大会優秀発表賞

2014/11　地理情報システム学会　地理的加重回帰分析を用いた新型インフルエンザの流行パターン解析：茨城県における公立小中学校の閉鎖措置実施データを用いて

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Papers 28

Strengthening Urban Pandemic Preparedness: A Dual-Focused Machine Learning-Enhanced Spatial Evaluation of Pandemic Vulnerability Through Infection Risk and Vaccination Accessibility Peer-reviewed

Dong Liu, Jason Gilliland, Tomoki Nakaya, Zihan Kan, Shohei Nagata, Jing Huang

Applied Spatial Analysis and Policy　19　1　2025/12/16
Publisher: Springer Science and Business Media LLC
DOI： 10.1007/s12061-025-09773-0 　

ISSN： 1874-463X

eISSN： 1874-4621

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Abstract Major pandemic outbreaks have profound global social and economic consequences, underscoring the urgency for cities to adopt adaptive preparedness strategies. During such outbreaks, municipal governments often implement broad containment measures, including mobility restrictions. While these measures are crucial for protecting public health, their application without a nuanced understanding of local pandemic conditions can disrupt socioeconomic systems and disproportionately burden communities. Effective strategies must therefore integrate localized assessments of pandemic vulnerability and precise, neighborhood-level responses to mitigate adverse social and economic impacts. Using data from the COVID-19 pandemic outbreak, this research develops a dual-focused framework to evaluate urban pandemic vulnerability through the intersecting lenses of infection risk and vaccination accessibility. The proposed framework integrates the Spatially-Tuned Poisson Regression machine learning technique to empirically calibrate the distance-decay parameter, allowing the vaccination accessibility model to better reflect the average pull of vaccination sites. Applied to the high-density urban context of Hong Kong, the analysis identifies localized vulnerability patterns at the smallest census unit level, revealing heightened pandemic vulnerabilities in areas of Kowloon, northern Hong Kong Island, and select new towns in the New Territories. These findings demonstrate how spatially explicit assessments prioritize neighborhoods for targeted risk identification and mitigation strategies, offering a transferable framework for precise outbreak response during future pandemic outbreaks.
モバイル空間統計を活用した水害時の避難者数推計に関する研究

山下慎二, マスエリック, 越村俊一, 永田彰平, 森田格

第34回地理情報システム学会学術研究発表大会講演論文集　D5-03　2025/11
Multiple hazards and population change in Japan’s Suzu City after the 2024 Noto Peninsula Earthquake Peer-reviewed

Shohei Nagata, Erick Mas, Yuriko Takeda, Tomoki Nakaya, Shunichi Koshimura

Progress in Disaster Science　25　100396　2025/01
Publisher: Elsevier BV
DOI： 10.1016/j.pdisas.2024.100396 　

ISSN： 2590-0617
Local effects of non-pharmaceutical interventions on mitigation of COVID-19 spread through decreased human mobilities in Japan: a prefecture-level mediation analysis Peer-reviewed

Shohei Nagata, Yuta Takahashi, Hiroki M. Adachi, Glen D. Johnson, Tomoki Nakaya

Scientific Reports　14　26996　2024/11

DOI： 10.1038/s41598-024-78583-0 　
人流データを用いた令和6年能登半島地震発生時の津波警報の効果評価

永田彰平, 足立浩基, マス・エリック, 武田百合子, 中谷友樹, 越村俊一

第33回地理情報システム学会学術研究発表大会講演論文集　D6-02　2024/10
人文地理学における人流データ活用の可能性と課題 Invited

永田彰平

愛知大学三遠南信地域連携研究センター紀要　(10)　44-46　2024/07
The 2004 Noto Peninsula Earthquake Tsunami - It's Generation, Propagation, Inundation, and Impact

Shunichi Koshimura, Bruno Adriano, Ayumu Mizutani, Erick Mas, Yusaku Ohta, Shohei Nagata, Yuriko Takeda, Ruben Vescovo, Sesa Wiguna, Takashi Abe, Takayuki Suzuki

2024/03/11

DOI： 10.5194/egusphere-egu24-22527 　
Tsunami Digital Twin - Concept, Progress, and Application to the 2024 Noto Peninsula Earthquake Tsunami Disaster, Japan Invited

Shunichi Koshimura, Bruno Adriano, Erick Mas, Shohei Nagata, Yuriko Takeda

2024/03/09

DOI： 10.5194/egusphere-egu24-14673 　
Enabling Space-Time Kernel Density Estimation in a 3D Geographic Information System Environment

Tomoki Nakaya, Shohei Nagata

Geographical reports of Tokyo Metropolitan University　59　41-48　2024/03
Urban Streetscape Changes in Portland, Oregon: A Longitudinal Virtual Audit Peer-reviewed

Tomoya Hanibuchi, Shohei Nagata, David Banis, Hunter Shobe, Tomoki Nakaya

The Professional Geographer　1-14　2024/01/31
Publisher: Informa UK Limited
DOI： 10.1080/00330124.2023.2287166 　

ISSN： 0033-0124

eISSN： 1467-9272
GPSデータから推計した歩行量分布と街路形態指標の関連性評価

渡邉怜央, 永田彰平, 中谷友樹

第32回地理情報システム学会講演論文集　2023/10
Development of a method for walking step observation based on large-scale GPS data International-journal Peer-reviewed

Shohei Nagata, Tomoki Nakaya, Tomoya Hanibuchi, Naoki Nakaya, Atsushi Hozawa

International Journal of Health Geographics　21　(1)　10-10　2022/09/07
Publisher: Springer Science and Business Media LLC
DOI： 10.1186/s12942-022-00312-5 　

eISSN： 1476-072X

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Abstract Background Widespread use of smartphones has enabled the continuous monitoring of people’s movements and physical activity. Linking global positioning systems (GPS) data obtained via smartphone applications to physical activity data may allow for large-scale and retrospective evaluation of where and how much physical activity has increased or decreased due to environmental, social, or individual changes caused by policy interventions, disasters, and infectious disease outbreaks. However, little attention has been paid to the use of large-scale commercial GPS data for physical activity research due to limitations in data specifications, including limited personal attribute and physical activity information. Using GPS logs with step counts measured by a smartphone application, we developed a simple method for daily walking step estimation based on large-scale GPS data. Methods The samples of this study were users whose GPS logs were obtained in Sendai City, Miyagi Prefecture, Japan, during October 2019 (37,460 users, 36,059,000 logs), and some logs included information on daily step counts (731 users, 450,307 logs). The relationship between land use exposure and daily step counts in the activity space was modeled using the small-scale GPS logs with daily step counts. Furthermore, we visualized the geographic distribution of estimated step counts using a large set of GPS logs with no step count information. Results The estimated model showed positive relationships between visiting high-rise buildings, parks and public spaces, and railway areas and step counts, and negative relationships between low-rise buildings and factory areas and daily step counts. The estimated daily step counts tended to be higher in urban areas than in suburban areas. Decreased step counts were mitigated in areas close to train stations. In addition, a clear temporal drop in step counts was observed in the suburbs during heavy rainfall. Conclusions The relationship between land use exposure and step counts observed in this study was consistent with previous findings, suggesting that the assessment of walking steps based on large-scale GPS logs is feasible. The methodology of this study can contribute to future policy interventions and public health measures by enabling the retrospective and large-scale observation of physical activity by walking.
COVID-19 case-clusters and transmission chains in the communities in Japan. International-journal Peer-reviewed

Yuki Furuse, Naho Tsuchiya, Reiko Miyahara, Ikkoh Yasuda, Eiichiro Sando, Yura K Ko, Takeaki Imamura, Konosuke Morimoto, Tadatsugu Imamura, Yugo Shobugawa, Shohei Nagata, Atsuna Tokumoto, Kazuaki Jindai, Motoi Suzuki, Hitoshi Oshitani

The Journal of Infection　84　(2)　248-288　2022/02

DOI： 10.1016/j.jinf.2021.08.016 　
時空間キューブを利用したCOVID-19流行の時空間地図

中谷友樹, 永田彰平

ESTRELA　336　(336)　2-7　2022

ISSN： 1343-5647
Relationships among changes in walking and sedentary behaviors, individual attributes, changes in work situation, and anxiety during the COVID-19 pandemic in Japan. International-journal Peer-reviewed

Shohei Nagata, Hiroki M Adachi, Tomoya Hanibuchi, Shiho Amagasa, Shigeru Inoue, Tomoki Nakaya

Preventive Medicine Reports　24　101640-101640　2021/12

DOI： 10.1016/j.pmedr.2021.101640 　

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Studies from many countries, including Japan, have reported decreased physical activity during the coronavirus disease 2019 (COVID-19) pandemic. However, the individual attributes as related to changes in physical activity during the pandemic in Japan have been scarcely investigated. The present study explored the relationships among individual attributes including demographic, socioeconomic, and geographic characteristics, work situation changes, perception of anxiety, and changes in walking and sedentary behaviors, during the pandemic in Japan. To obtain data indicating individual circumstances during the first wave of the pandemic in Japan, we conducted a nationwide online survey from May 19 to May 23, 2020 (n = 1,200). To observe changes in walking behavior objectively and retrospectively, we collected data on the number of daily steps as measured by the iPhone's Health application. Path analysis was employed to examine relationships between individual attributes and changes in walking and sedentary behaviors. Decreased physical activity, especially, decreased walking behavior among younger individuals and those living in highest-density neighborhoods were identified. There was increased sedentary behavior among females. Moreover, individuals with higher socioeconomic status (SES) tended to become inactive due to work-from-home/standby-at-home and individuals with lower SES tended to become inactive due to decreased amount of work. Decreased walking behavior and increased sedentary behavior were associated with a perception of strong anxiety related to the pandemic. Our findings would be helpful in considering measures to counteract health risks during the pandemic by taking into account individual backgrounds.
Coastal exposure and residents' mental health in the affected areas by the 2011 Great East Japan Earthquake and Tsunami. International-journal Peer-reviewed

Ai Tashiro, Mana Kogure, Shohei Nagata, Fumi Itabashi, Naho Tsuchiya, Atsushi Hozawa, Tomoki Nakaya

Scientific Reports　11　(1)　16751-16751　2021/08/18

DOI： 10.1038/s41598-021-96168-z 　

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No previous study has ever explored the association between coastal exposure and the mental health of residents in a post-disaster context. Therefore, we aimed to confirm whether there was an association between sea visibility and coastal proximity and the mental health of coastal residents a devastating tsunami. We targeted 15 coastal municipalities located in the Miyagi Prefecture, and obtained data from a community-based cohort study. The baseline survey was initiated 2 years after the 2011 Great East Japan Earthquake and Tsunami and the secondary survey was initiated 6 years after the disaster. We applied multilevel mixed-effects models to the longitudinal data. Our outcome measure was the Kessler Psychological Distress Scale (K6) score. We assessed the data collected from 2,327 respondents on both surveys as of April 2018 for this ongoing cohort study. We found that neither sea visibility nor coastal proximity was significantly associated with the recovery of mental health after the disaster. However, we found a distinctive trend of mental health recovery in people who lived alone with a sea view, indicating that visibility of the sea had a negative effect on their mental health immediately after the GEJET, but that the negative effect was subsequently eliminated.
Mobility Change and COVID-19 in Japan: Mobile Data Analysis of Locations of Infection. Peer-reviewed

Shohei Nagata, Tomoki Nakaya, Yu Adachi, Toru Inamori, Kazuto Nakamura, Dai Arima, Hiroshi Nishiura

Journal of Epidemiology　31　(6)　387-391　2021/06/05

DOI： 10.2188/jea.JE20200625 　

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BACKGROUND: As the COVID-19 pandemic spread, the Japanese government declared a state of emergency on April 7, 2020 for seven prefectures, and on April 16, 2020 for all prefectures. The Japanese Prime Minister and governors requested people to adopt self-restraint behaviors, including working from home and refraining from visiting nightlife spots. However, the effectiveness of the mobility change due to such requests in reducing the spread of COVID-19 has been little investigated. The present study examined the association of the mobility change in working, nightlife, and residential places and the COVID-19 outbreaks in Tokyo, Osaka, and Nagoya metropolitan areas in Japan. METHODS: First, we calculated the daily mobility change in working, nightlife, and residential places compared to the mobility before the outbreak using mobile device data. Second, we estimated the sensitivity of mobility changes to the reproduction number by generalized least squares. RESULTS: Mobility change had already started in March, 2020. However, mobility reduction in nightlife places was particularly significant due to the state of emergency declaration. Although the mobility in each place type was associated with the COVID-19 outbreak, the mobility changes in nightlife places were more significantly associated with the outbreak than those in the other place types. There were regional differences in intensity of sensitivity among each metropolitan area. CONCLUSIONS: Our findings indicated the effectiveness of the mobility changes, particularly in nightlife places, in reducing the outbreak of COVID-19.
Relationship between Internet use and out-of-home activities during the first wave of the COVID-19 outbreak in Japan. International-journal Peer-reviewed

Naoto Yabe, Tomoya Hanibuchi, Hiroki M Adachi, Shohei Nagata, Tomoki Nakaya

Transportation Research Interdisciplinary Perspectives　10　100343-100343　2021/06

DOI： 10.1016/j.trip.2021.100343 　

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Following the first wave of the COVID-19 outbreak, the Japanese government announced the declaration of a state of emergency in April 2020, which aimed to decrease contact between people and requested that residents refrain from outings. Even in the absence of penalties, outings decreased under the declaration. We are interested in how outings declined and studied the substitution relationship between Internet use and outings. A web-based survey was conducted to collect data on Internet use and outings in a retrospective manner. The period covered by our data is from mid-February to mid-May 2020. Multilevel analysis and binomial logistic regression analysis were performed to examine the relationship between Internet use and outings. The results clearly show that Internet use replaced outings. In particular, Internet use for socializing, exercise, and leisure/entertainment had a strong substitution relationship with outings. Internet use for socializing and leisure/entertainment was also associated with refraining from visiting restaurants. In contrast, there was a weak substitution relationship between Internet use for daily shopping and outings. Although telework tends to be an accepted focus of Internet use under the COVID-19 outbreak, it should not be overlooked that other uses of the Internet, such as for leisure/entertainment, also supported the decline in outings.
Types of coastlines and the evacuees' mental health: A repeated cross-sectional study in Northeast Japan. International-journal Peer-reviewed

Ai Tashiro, Tomoki Nakaya, Shohei Nagata, Jun Aida

Environmental Research　196　110372-110372　2021/05

DOI： 10.1016/j.envres.2020.110372 　

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Although the health risks and benefits of coastal areas have long been researched, these effects of the different types of coastlines have rarely been explored on the evacuees living near the coast, in a post-disaster context. Thus, this study aimed to explore, with the passing of years after a disaster, what kind of coastline is a useful public health resource as a post-disaster reconstruction approach in coastal environments that have suffered significantly from the tsunami disaster in northeast Japan in 2011. This study compared the evacuees' mental health based on proximity to the coast and the types of coastlines (artificial, semi-natural, and natural). Data were drawn from the Miyagi Prefectural Government surveys, which targeted almost all evacuees of the 2011 Great East Japan Earthquakes and Tsunami (n = 96,203). We applied a pooled Poisson regression model to a repeated cross-sectional dataset of evacuees' mental health between 2012 and 2016. Moderate psychological distress, measured via the Kessler Psychological Distress Scale (K6) score, was the dependent variable, while proximity to the coast and type of coastline were the independent variables. The estimated main effects of type of coastline indicated that overall associations between K6 ≥5 and all types of coastlines within a 1.6 km buffer of participants' residential space were not statistically significant (p > 0.05). However, among types of coastlines, the interaction terms of semi-natural coastline × year (2015 and 2016) were significantly associated with lower incidence rate ratios (IRR), which decreased in 2015 and 2016 (IRR: 0.88, 95%CI: 0.79-0.98; IRR: 0.78, 95%CI: 0.68-0.90, respectively). Further, we computed the marginal effects of coastline types for each year to observe differences in the impact on moderate psychological distress depending on different accessible coastline types within a distance of 1.6 km from the participants' living space. We found that, after the revision of the coastal act in 2014, the moderate mental stress of participants who lived around semi-natural coastlines significantly tended to be low (dy/dx: -0.04, 95%CI: -0.08-0.01 in 2015; dy/dx: -0.07, 95%CI: -0.11-0.04 in 2016). This finding can encourage policymakers to manage coastal areas with green infrastructure in the post-disaster reconstruction sustainably.
Familial Clusters of Coronavirus Disease in 10 Prefectures, Japan, February-May 2020. International-journal Peer-reviewed

Reiko Miyahara, Naho Tsuchiya, Ikkoh Yasuda, Yura K Ko, Yuki Furuse, Eiichiro Sando, Shohei Nagata, Tadatsugu Imamura, Mayuko Saito, Konosuke Morimoto, Takeaki Imamura, Yugo Shobugawa, Hiroshi Nishiura, Motoi Suzuki, Hitoshi Oshitani

Emerging Infectious Diseases　27　(3)　915-918　2021/03

DOI： 10.3201/eid2703.203882 　

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The overall coronavirus disease secondary attack rate (SAR) in family members was 19.0% in 10 prefectures of Japan during February 22-May 31, 2020. The SAR was lower for primary cases diagnosed early, within 2 days after symptom onset. The SAR of asymptomatic primary cases was 11.8%.
COVID-19流行の空間疫学 : コロナ禍の地理学

学術の動向 = Trends in the sciences　26　(11)　60-67　2021
Publisher: 日本学術協力財団
ISSN： 1342-3363
iPhoneのヘルスケアアプリとインターネット調査を用いた歩数計測の新しい方法の開発：COVID-19流行に対する緊急事態宣言前後の歩数変化調査を事例に Peer-reviewed

足立浩基, 埴淵知哉, 永田彰平, 天笠志保, 井上茂, 中谷友樹

運動疫学研究　23　(2)　172-182　2021
Publisher: 日本運動疫学会
ISSN： 1347-5827

eISSN： 2434-2017
Objective scoring of streetscape walkability related to leisure walking: Statistical modeling approach with semantic segmentation of Google Street View images. International-journal Peer-reviewed

Shohei Nagata, Tomoki Nakaya, Tomoya Hanibuchi, Shiho Amagasa, Hiroyuki Kikuchi, Shigeru Inoue

Health & Place　66　102428-102428　2020/11

DOI： 10.1016/j.healthplace.2020.102428 　

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Although the pedestrian-friendly qualities of streetscapes promote walking, quantitative understanding of streetscape functionality remains insufficient. This study proposed a novel automated method to assess streetscape walkability (SW) using semantic segmentation and statistical modeling on Google Street View images. Using compositions of segmented streetscape elements, such as buildings and street trees, a regression-style model was built to predict SW, scored using a human-based auditing method. Older female active leisure walkers living in Bunkyo Ward, Tokyo, are associated with SW scores estimated by the model (OR = 3.783; 95% CI = 1.459 to 10.409), but male walkers are not.
Clusters of Coronavirus Disease in Communities, Japan, January-April 2020. International-journal Peer-reviewed

Yuki Furuse, Eiichiro Sando, Naho Tsuchiya, Reiko Miyahara, Ikkoh Yasuda, Yura K Ko, Mayuko Saito, Konosuke Morimoto, Takeaki Imamura, Yugo Shobugawa, Shohei Nagata, Kazuaki Jindai, Tadatsugu Imamura, Tomimasa Sunagawa, Motoi Suzuki, Hiroshi Nishiura, Hitoshi Oshitani

Emerging Infectious Diseases　26　(9)　2176-9　2020/09

DOI： 10.3201/eid2609.202272 　

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We analyzed 3,184 cases of coronavirus disease in Japan and identified 61 case-clusters in healthcare and other care facilities, restaurants and bars, workplaces, and music events. We also identified 22 probable primary case-patients for the clusters; most were 20-39 years of age and presymptomatic or asymptomatic at virus transmission.
機械学習に基づいたストリートレベルのウォーカビリティ評価－Google Street View画像を対象として

永田彰平, 中谷友樹, 埴淵知哉

地理情報システム学会講演論文集　28　2019
地理情報システムを用いたウォーカビリティ指数の作成に関するノート

中谷友樹, 前田一馬, 永田彰平

2018/03
地理的加重回帰分析を用いた新型インフルエンザの流行パターン解析:茨城県における公立小中学校の閉鎖措置実施データを用いて

永田彰平, 中谷友樹

地理情報システム学会講演論文集　23　2014
新型インフルエンザ流行時における学校閉鎖措置の時空間的パターン:2009-2010年シーズンの茨城県における公立小中学校の学校閉鎖措置に注目して

永田彰平, 中谷友樹

地理情報システム学会講演論文集　22　2013

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Misc. 19

Changes in Urban Human Mobility by Deprivation Level during the COVID-19 Pandemic in Japan

Shohei Nagata, Clive Sabel, Tomoki Nakaya

International Conference on Urban Health 2024: Abstract Book　2024/11
Measurement of spatial population changes due to disaster using cell phone-based data: A case study of the 2024 Noto Peninsula Earthquake in Japan

Shohei Nagata, Erick Mas, Yuriko Takeda, Tomoki Nakaya, Shunichi Koshimura

Book Of Abstracts for 2024 International Conference on Resilient Systems　77-77　2024/10

DOI： 10.3929/ethz-b-000696625 　
More than 10,000 Maps Reveal the Asia-Pacific Past in Greater Detail

Yukihisa Hoshida, Ryohei Sekine, Yuzuru Isoda, Shohei Nagata, Tomoki Nakaya

ArcUser Summer 2024　27　(3)　28-31　2024/08
The Impact of the 2024 Noto Peninsula Earthquake Tsunami

Shunichi Koshimura, Bruno Adriano, Ayumu Mizutani, Erick Mas, Yusaku Ohta, Shohei Nagata, Yuriko Takeda, Ruben Vescovo, Sesa Wiguna, Takashi Abe, Takayuki Suzuki

Abstract EGU24-22523　2024/03/11
Publisher: Copernicus GmbH
DOI： 10.5194/egusphere-egu24-22523 　

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The tsunami generated by the Mw7.6 earthquake of Noto Peninsula, Japan left widespread impact. We analyzed multi-modal information and data to elucidate its impact.We modeled the tsunami propagation and inundation with multiple tsunami source models based on GNSS-based crustal movement and tsunami waveform data to understand its propagation and inundation characteristics. The model results are verified by using post-tsunami field survey data. Preliminary tsunami modeling results implied that severe tsunami impacts were around Noto Peninsula (Shika to Nanao). Through the visualization of tsunami propagation model, we found that the remarkable tsunami refraction around the continental shelf of Noto Peninsula were responsible for high tsunamis in Suzu City. This distinctive sea bottom topography also affected the directivity of tsunami energy toward the Japan sea coasts, especially Joetsu city, Nigata Prefecture. Tsunami in Toyama bay had long duration of oscillation caused by multiple-reflection. The leading (negative) tsunami wave could not be explained by fault rupture and this implied the possibility of submarine landslides.The post-tsunami field survey teams at Suzu City preliminarily found tsunami run-ups of 3 m or higher with flow depths of 2.5m or higher. Inside the tsunami inundation zone around Noto Peninsula, we found at least 648 houses out of 3398 were destroyed by both the strong ground motion and tsunami.The cellphone-based population data (Mobile Spatial Statistics) were used to analyze the exposed population in the aftermath of the event. The hourly population estimates with 500m spatial resolution in the coastal communities implied how people reacted and were affected. Approximately 2500 population increase were found in the areas above 10 m after the major tsunami warning was issued.
日本におけるCOVID-19関連死亡の地理的格差 2020年の市区町村スケールでの解析

中谷友樹, 永田彰平, 埴淵知哉, 伊藤ゆり

Journal of Epidemiology　33　(Suppl.1)　81-81　2023/02
人流データの身体活動研究への活用 Invited

72　(1)　113-113　2023
Publisher: The Japanese Society of Physical Fitness and Sports Medicine
DOI： 10.7600/jspfsm.72.113 　

ISSN： 0039-906X

eISSN： 1881-4751
Where have Japanese COVID-19 outbreaks been sustained?

Tomoki Nakaya, Shohei Nagata

Esri Map Book　37　80-81　2022/07
地理的はく奪指標とCOVID-19流行の関連：首都圏の市区町村を対象に

永田彰平, 髙勇羅, 中谷友樹, 押谷仁

第32回日本疫学会学術総会講演集　2022
新型コロナウィルス感染症の流行状況を可視化するGISの有用性

中谷友樹, 永田彰平

『地理総合』学校教育支援サイト教材素材集　2022
GIS mapping of COVID-19 pandemic

4　(7)　615-618　2021/07
Publisher: 北隆館
ISSN： 2434-3625
健康的な近隣環境を測る―街路景観ウォーカビリティを対象として― Invited

永田彰平

GIS Next　74　55　2021
クラウドソーシングによる系統的・仮想的社会観察

埴淵知哉, 永田彰平, バニスデービッド, ショービーハンター, 中谷友樹

日本地理学会発表要旨集　2020
深層学習に基づく街路景観評価指標と歩行量との関連

永田彰平, 中谷友樹, 埴淵知哉, 天笠志保, 菊池宏幸, 井上茂

第30回日本疫学会学術総会講演集　2020
モバイルデバイスデータを用いたCOVID-19流行とモビリティ変化の関連の分析

永田彰平, 中谷友樹, 菖蒲川由郷

日本地理学会発表要旨集　2020
Finding Lost Landscapes in Southeast Asia

Yukihisa Hoshida, Tomoki Nakaya, Shohei Nagata, Yuzuru Isoda, Ryohei Sekine

ArcUser　23　(4)　66-70　2020
Space-time mapping of historical plague epidemics in modern Osaka, Japan

Tomoki Nakaya, Kazumasa Hanaoka, Shohei Nagata

Abstracts of the International Cartographic Association　2019
2010〜2013年における徒歩フードアクセスの喪失地区

永田彰平, 中谷友樹, 矢野桂司, 秋山祐樹

2015
南海トラフ地震発生時における津波による文化財被災リスク評価

前田一馬, 中谷友樹, 永田彰平

日本地理学会発表要旨集　2015
新型インフルエンザ流行の空間的伝播モデリング:茨城県における公立小中学校の閉鎖措置実施データを用いて

永田彰平, 中谷友樹

日本地理学会発表要旨集　2015

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Presentations 49

Population Change in Japan's Coastal Areas During Tsunami Advisories and Warnings Following the 2025 Kamchatka Earthquake

Shohei Nagata, Hiroki M. Adachi, Erick Mas, Yuriko Takeda, Tomoki Nakaya, Cynthia Chen, Lyra Chen, Shunichi Koshimura

2026 AAG Annual Meeting　2026/03/19
Quantifying Human Mobility Changes During and After the 2024 Noto Peninsula Earthquake and Tsunami Using Mobile Phone Network Data in Japan

Shohei Nagata, Erick Mas, Wei Yuan, Shunichi Koshimura, Cynthia Chen, Lyra Chen

AGU25　2025/12/16
モバイル空間統計を活用した水害時の避難者数推計に関する研究

山下慎二, マスエリック, 越村俊一, 永田彰平, 森田格

第34回地理情報システム学会学術研究発表大会　2025/11/02
感染症流行や自然災害下における人流データ解析 Invited

永田彰平

日本学術会議地域研究委員会地域情報分科会公開シンポジウム「人流ビッグデータがもたらす新しい未来像」　2025/03/01
Changes in Urban Human Mobility by Deprivation Level during the COVID-19 Pandemic in Japan

Shohei Nagata, Clive Sabel, Tomoki Nakaya

International Conference on Urban Health 2024　2024/11/19
人流データを用いた令和6年能登半島地震発生時の津波警報の効果評価

永田彰平, 足立浩基, マスエリック, 武田百合子, 中谷友樹, 越村俊一

第33回地理情報システム学会学術研究発表大会　2024/10/27
Analysis of Population Changes after the 2024 Noto Peninsula Earthquake in Japan Invited

Shohei Nagata

Expert Seminar on “Effective Evacuation in Earthquake or Tsunami Situations”　2024/09/24
Measurement of spatial population changes due to disaster using cellphone-based data: A case study of the 2024 Noto Peninsula Earthquake in Japan

Shohei Nagata, Erick Mas, Yuriko Takeda, Tomoki Nakaya, Shunichi Koshimura

International Conference on Resilient Systems 2024　2024/08/30
Development of synthetic trajectory data based on ambient population and GPS data

Shohei Nagata, Hiroki M. Adachi, Kazumasa Hanaoka, Yuriko Takeda, Tomoki Nakaya, Shunichi Koshimura

The 5th International Time-Geography Conference　2024/08/04
Analysis of Human Traffic Data in Traditional Japanese Festivals

Hirotaka Sato, Shohei Nagata, Yong Jiang, Nobuhiko Komaki

The 5th International Time-Geography Conference　2024/08/03
GPSデータとモバイル空間統計に基づく個人レベルの合成人流データの構築

永田彰平

東北大学災害科学国際研究所 2023年度災害レジリエンス共創研究報告会　2024/07/26
Comparison of tsunami-exposed populations based on static and dynamic population data

Shohei Nagata, Erick Mas, Yuriko Takeda, Shinji Kataya, Naomichi Kuwahara, Tomoki Nakaya, Shunichi Koshimura

2024 AAG Annual Meeting　2024/04/17
令和6年能登半島地震発生後の人流変化

永田彰平, マス・エリック, 武田百合子, 越村俊一

2024年日本地理学会春季学術大会【緊急公開シンポジウム】令和6年能登半島地震　2024/03/19
GPSデータとモバイル空間統計に基づく合成人流データの構築

永田彰平, 足立浩基, 花岡和聖, 武田百合子, 中谷友樹, 越村俊一

2023年度地理情報システム学会東北支部研究交流会　2024/03/13
人流データ活用の可能性と課題 Invited

永田彰平

第11回越境地域政策研究フォーラム　2024/02/10
社会経済的居住分離と健康行動の履歴の格差：ライフコース回顧調査資料の配列解析

中谷友樹, 永田彰平, 埴淵知也

第34回日本疫学会学術総会　2024/02/01
GPSデータを用いて推定した歩行量と経路の居住地環境による地域差

渡邉怜央, 永田彰平, 中谷友樹

第34回日本疫学会学術総会　2024/02/01
非薬物的介入実施の人流抑制を介したCOVID-19流行緩和効果: 47都道府県別の評価

永田彰平, 髙橋侑太, 足立浩基, Glen D. Johnson, 中谷友樹

第34回日本疫学会学術総会　2024/02/02
GPSデータから推計した歩行量分布と街路形態指標の関連性評価

渡邉怜央, 永田彰平, 中谷友樹

第32回地理情報システム学会学術研究発表大会　2023/10/29
Real-time mapping of population exposure to tsunami hazard from human mobility data

Erick Mas, Shinji Kataya, Naomichi Kuwahara, Yuriko Takeda, Shohei Nagata, Shunichi Koshimura
Changing Catchment of People Flows: mapping the variety of where visitors live over Japan

Shohei Nagata, Tomoki Nakaya, Yuriko Takeda, Shunichi Koshimura

2023/07/10
人流変化を媒介した非薬物的介入のCOVID-19流行への影響評価

永田彰平, 高橋侑太, 足立浩基, 中谷友樹

日本地理学会2023年春季学術大会　2023/03/26
COVID-19流行時の人流変化と感染の関係 Invited

永田彰平

SDGS-ID 公開シンポジウム「COVID-19と学際研究」　2023/03/18
高解像度な空間単位でのCOVID-19流行予測アプリケーションの開発

永田彰平, 足立浩基, 藤原直哉, 中谷友樹

第31回地理情報システム学会研究発表大会
人流データの身体活動研究への応用 Invited

永田彰平

第77回日本体力医学会『身体活動研究におけるICTの活用』　2022/09/22
Assessing socio-spatial disparities of COVID-19 related mortality in Japan

11th International Conference on Population Geographies, Tokyo, 26 Aug 2022　2022/08/26
地理的はく奪指標とCOVID-19流行の関連：首都圏の市区町村を対象に

永田彰平, 髙勇羅, 中谷友樹, 押谷仁

第32回日本疫学会学術総会　2022/01
人流データを利用したCOVID-19流行の微細な時空間モデル

中谷友樹, 足立浩基, 永田彰平, 藤原直哉

第30回地理情報システム学会研究発表大会　2021/10
仙台市における歩行場所の空間的特性：GPSログを用いた分析

永田彰平, 中谷友樹, 埴淵知哉, 中谷直樹, 寳澤篤

第30回地理情報システム学会研究発表大会　2021/10
Gaihozu Viewer: Indonesian-territory version - Historical maps made by former Japanese Imperial Army

Ryohei Sekine, Tomoki Nakaya, Shohei Nagata, Yuzuru Isoda, Yukihisa Hoshida

Esri User Conference, Map Gallery　2021/07
COVID-19 Spatio-temporal Case-Density Map: Where Have the COVID-19 Outbreaks Been Sustained in Japan?

Tomoki Nakaya, Shohei Nagata

Esri User Conference, Map Gallery　2021/07
COVID-19流行はDOKODE続いているか：COVID-19時空間３Dマップ

中谷友樹, 永田彰平

第17回GISコミュニティフォーラムマップギャラリー2021　2021/05
緊急事態宣言に伴う身体活動の変化：新型コロナウイルス感染症第一波を対象として

永田彰平, 足立浩基, 埴淵知哉, 天笠志保, 井上茂, 中谷友樹

東北地理学会 2021年度春季学術大会　2021/05
Mobility change and physical inactivity due to the COVID-19 outbreak in Japan Invited

Shohei Nagata

International Young Researchers Symposium, Urbanism in the Age of COVID-19: Toward an Inclusive and Resilient Society　2021/03/20
新型コロナウイルス感染症流行対策におけるGIS活用―時空間マップ作成までの裏側― Invited

永田彰平

ESRIジャパン株式会社, 地図を活用した新型コロナウイルス対策ウェビナー　2021/03
COVID-19流行とモビリティ変化の関連：モバイルデバイスデータに基づく分析

永田彰平, 中谷友樹

2020年度地理情報システム学会東北支部研究交流会　2021/03
COVID-19流行とモビリティ変化の関連：モバイルデバイスデータに基づく分析

永田彰平, 中谷友樹

東北大学理学・生命科学2研究科合同オンラインシンポジウム2021　2021/02
モバイルデバイスデータを用いたCOVID-19流行とモビリティ変化の関連の分析 Invited

永田彰平, 中谷友樹, 菖蒲川由郷

日本地理学会2020年秋季学術大会特別セッション「COVID-19と地理学」　2020/11
緊急事態宣言と歩数の地域的変化－iPhoneのヘルスケアアプリを利用した歩数調査法を用いて－

足立浩基, 埴淵知哉, 永田彰平, 天笠志保, 井上茂, 中谷友樹

2020年度東北地理学会秋季学術大会　2020/10
クラウドソーシングによる系統的・仮想的社会観察

埴淵知哉, 永田彰平, デービッドバニス, ハンターショービー, 中谷友樹

日本地理学会2020年春季学術大会　2020/03
深層学習に基づく街路景観評価指標と歩行量との関連

永田彰平, 中谷友樹, 埴淵知哉, 天笠志保, 菊池宏幸, 井上茂

日本疫学会第30回学術総会　2020/02
機械学習に基づいたストリートレベルのウォーカビリティ評価－Google Street View画像を対象として

永田彰平, 中谷友樹, 埴淵知哉

第28回地理情報システム学会研究発表大会　2019/10
Space-time mapping of historical plague epidemics in modern Osaka, Japan

Tomoki Nakaya, Kazumasa Hanaoka, Shohei Nagata

International Cartographic Conference 2019　2019/07/18
Evaluation of Neighborhood Walkability Using Google Street View and Deep Learning Approach

Shohei Nagata, Tomoki Nakaya, Tomoya Hanibuchi

18th International Medical Geography Symposium　2019/07/01
南海トラフ地震発生時における津波による文化財被災リスク評価

前田一馬, 中谷友樹, 永田彰平

日本地理学会2015年秋季学術大会　2015/09
新型インフルエンザ流行の空間的伝播モデリング―茨城県における公立小中学校の閉鎖措置データを用いて―

永田彰平, 中谷友樹

日本地理学会2015年春季学術大会　2015/03
地理的加重回帰分析を用いた新型インフルエンザの流行パターン解析：茨城県における公立小中学校の閉鎖措置実施データを用いて

永田彰平, 中谷友樹

第23回地理情報システム学会研究発表大会　2014/11
新型インフルエンザ流行時における学校閉鎖措置の時空間的パターン：2009-2010年シーズンの茨城県における公立小中学校の学校閉鎖措置に注目して

永田彰平, 中谷友樹

第22回地理情報システム学会研究発表大会　2013/10
Enhancing Tsunami Evacuation Modeling Using Human Mobility Analytics: Integrating Geographic, Psychological, and Data Science Perspectives

Ryo Saito, Shohei Nagata, Hiroki Adachi

2025 AI So-Go-Chi Symposium　2026/03/23

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Research Projects 11

地理総合に向けた歴史上のテーマを活用した防災教育の教材開発

根元裕樹, 夏目宗幸, 永田彰平

Offer Organization: 日本学術振興会

System: 科学研究費助成事業

Category: 基盤研究(C)

Institution: 東京都立大学

2025/04 - 2030/03
疫学・病原体ゲノム・人流データの融合によるCOVID-19感染拡大様式の解明

今村剛朗, 佐山勇輔, 永田彰平, 中谷友樹, 神垣太郎

Offer Organization: 日本学術振興会

System: 科学研究費助成事業

Category: 基盤研究(B)

Institution: 東北大学

2025/04 - 2028/03
健康の都市農村格差を計測する都市ー農村連続体指標の開発

中谷友樹, 永田彰平, 田淵貴大, 磯田弦, 関根良平, 寺床幸雄, 谷本涼, 伊藤ゆり

Offer Organization: 日本学術振興会

System: 科学研究費助成事業

Category: 基盤研究(B)

Institution: 東北大学

2025/04 - 2028/03
大規模GPSデータを用いた活動空間に基づくウォーカビリティと歩行量の関係の解明

永田彰平

Offer Organization: 日本学術振興会

System: 科学研究費助成事業若手研究

Category: 若手研究

Institution: 東北大学

2023/04 - 2027/03
令和6年能登半島地震発生時の人流解析に基づく津波避難モデルの構築と津波避難計画の最適化

Offer Organization: 東北大学

System: 若手リーダー海外派遣プログラム

2025/11 - 2026/09
人流データ活用による津波避難行動モデリングの精緻化：地理学、心理学、データ科学的アプローチの融合

齋藤玲, 足立浩基

Offer Organization: 東北大学総合知インフォマティクス研究センター

System: 総合知インフォマティクス研究センター研究助成

2025/04 - 2026/04
Developing a Mobile Phone Network Data-Driven Methodology to Quantify Community Resilience in Disaster Affected Areas

Shohei Nagata, Cynthia Chen, Erick Mas, Wei Yuan, Shunichi Koshimura, Lyra Chen

Offer Organization: Tohoku University

System: Tohoku University-University of Washington Strategic Partner Fund 2024-25

2025/04 - 2026/03
Enabling Human-Centered Digital Twin for Community Resilience Competitive

Erick Mas, Bruno Adriano, Shohei Nagata, Nalini Venkatasubramanian, Magaly Koch, Ron Eguchi

Offer Organization: Japan Science and Technology Agency (JST)

System: Strategic International Collaborative Research Program

Institution: International Research Institute of Disaster Science, Tohoku University

2024/04 - 2026/03

More details Close

The purpose of this research project is to apply and expand the concept of “Digital Twins” to disaster science and build a “Disaster Digital Twin” (DDT) which utilizes human-centered data to improve community resilience. Specifically, the DDT and a multi-agent simulation framework developed by the Japanese team will be applied in a context of the elderly, a population with personalized care needs which is disproportionately affected by disasters. This will be done through the integration of the “CareDEX” by the U.S. team, a platform which incorporates personalized care information from responders, caregivers and the elderly, with a digital twin developed by the both teams. This integration of technology developed by the two teams is expected to enable a variety of “Virtual Disaster City” (VDC) simulations which will be useful for policy design in for the elderly with the specific needs, for example medical equipment, reduced mobility, cognitive disease, in a context of disaster resilience.
合成人流データを用いた令和6年能登半島地震発生時の津波避難モデルの構築

永田彰平, 中谷友樹, 足立浩基, 武田百合子, 越村俊一, 花岡和聖, 齋藤玲, 大内啓樹

Offer Organization: 東北大学災害科学国際研究所災害レジリエンス共創センター

System: 災害レジリエンス共創研究プロジェクト

2024/06 - 2025/03
地理学と心理学の融合による津波避難行動モデルの精緻化：令和6年能登半島地震発生時の人流解析を通して

齋藤玲

Offer Organization: 東北大学総合知インフォマティクス研究センター

System: 総合知インフォマティクス研究センター研究助成

2024/04 - 2025/03
GPSデータとモバイル空間統計に基づく個人レベルの合成人流データの構築

永田彰平, 中谷友樹, 足立浩基, 武田百合子, 越村俊一, 花岡和聖

Offer Organization: 東北大学災害科学国際研究所災害レジリエンス共創センター

System: 災害レジリエンス共創研究プロジェクト

2023/06 - 2024/03

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Teaching Experience 2

地理情報解析学実習　東北大学
自然環境地理学　東北大学

Works 2

Changing Catchment of People Flows: mapping the variety of where visitors live over Japan

Shohei Nagata, Tomoki Nakaya, Yuriko Takeda, Shunichi Koshimura

2023/07/10 -

Type: Web Service
COVID-19 Spatio-temporal case-density map

永田彰平, 中谷友樹

2020/12 -

Type: Web Service

Social Activities 2

厚生労働省新型コロナウイルス対策本部クラスター対策班参与

2020/02 - 2021/03
日本計算機統計学会第37回シンポジウムチュートリアル「健康まちづくりとWalkabilityーPythonでGISー」

2023/11/10 -